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March 1, 2022 22:26
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Omniglot example for Autobots: Latent Variable Sequential Set Transformers
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{ | |
"nbformat": 4, | |
"nbformat_minor": 0, | |
"metadata": { | |
"colab": { | |
"name": "autobot_omniglot.ipynb", | |
"provenance": [], | |
"collapsed_sections": [ | |
"vHBx9L924APp", | |
"jl8rVC3x4q0M", | |
"qihb0PM-4kte", | |
"5yRdFh2R48_P", | |
"6Qf-IiT8646l", | |
"8m8q_EM_7DuV" | |
] | |
}, | |
"kernelspec": { | |
"name": "python3", | |
"display_name": "Python 3" | |
}, | |
"language_info": { | |
"name": "python" | |
}, | |
"accelerator": "GPU" | |
}, | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "dX5V-W5036Cq" | |
}, | |
"source": [ | |
"# Autobot for Character Generation" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "MIVW1za6R_42" | |
}, | |
"source": [ | |
"This Jupyter notebook contains a standalone demonstration of the AutoBot method/architecture applied to the Omniglot stroke-completion task (\"task 1\" in the paper). This means, we download the Omniglot stroke dataset, and train to complete character strokes by showing the model the first half of a stroke and training it to predict the second half." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "XOyNUeBDWQu4" | |
}, | |
"source": [ | |
"This notebook has the following sections:\n", | |
"\n", | |
"\n", | |
"\n", | |
"1. [Downloading the Omniglot dataset and preparing the data](#scrollTo=vHBx9L924APp)\n", | |
"2. [Creating a dataloader for Pytorch to prepare the data for training/testing](#scrollTo=jl8rVC3x4q0M)\n", | |
"3. [Setting up the Autobot model](#scrollTo=qihb0PM-4kte)\n", | |
"4. [Setting up the loss functions](#scrollTo=5yRdFh2R48_P)\n", | |
"5. [Training the model (est 45-60min)](#scrollTo=6Qf-IiT8646l)\n", | |
"6. [Plot/test functions to generate qualitative samples from the trained model on the test dataset](#scrollTo=8m8q_EM_7DuV)\n", | |
"\n", | |
"This notebook should contain a trained model and if you scroll all the way to the end of the test section, there should be sample images. If that's not the case, please rerun the entire notebook.\n", | |
"\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "vHBx9L924APp" | |
}, | |
"source": [ | |
"## Setting Up the Omniglot dataset\n", | |
"In the section, we download and process the Omniglot dataset to generate and training and testing partitions." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "gGs7GVjbqmy1", | |
"outputId": "df231b1e-20ac-4992-b673-3e0e7522abfa" | |
}, | |
"source": [ | |
"!git clone https://github.com/brendenlake/omniglot.git\n", | |
"!unzip \"omniglot/python/images_background.zip\"\n", | |
"!unzip \"omniglot/python/images_evaluation.zip\"\n", | |
"!unzip \"omniglot/python/strokes_background.zip\"\n", | |
"!unzip \"omniglot/python/strokes_evaluation.zip\"" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"text": [ | |
"Cloning into 'omniglot'...\n", | |
"remote: Enumerating objects: 81, done.\u001b[K\n", | |
"remote: Total 81 (delta 0), reused 0 (delta 0), pack-reused 81\u001b[K\n", | |
"Unpacking objects: 100% (81/81), done.\n" | |
], | |
"name": "stdout" | |
} | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "LZBPUhfLsOh0", | |
"outputId": "cd3f0bea-5a2a-425c-9b88-c3465abd9b68" | |
}, | |
"source": [ | |
"import numpy as np\n", | |
"import os\n", | |
"import random\n", | |
"from sys import platform as sys_pf\n", | |
"\n", | |
"\n", | |
"# Color map for the stroke of index k\n", | |
"def get_color(k):\n", | |
" scol = ['r', 'g', 'b', 'm', 'c']\n", | |
" ncol = len(scol)\n", | |
" if k < ncol:\n", | |
" out = scol[k]\n", | |
" else:\n", | |
" out = scol[-1]\n", | |
" return out\n", | |
"\n", | |
"\n", | |
"# convert to str and add leading zero to single digit numbers\n", | |
"def num2str(idx):\n", | |
" if idx < 10:\n", | |
" return '0' + str(idx)\n", | |
" return str(idx)\n", | |
"\n", | |
"\n", | |
"# Load binary image for a character\n", | |
"#\n", | |
"# fn : filename\n", | |
"def load_img(fn):\n", | |
" I = plt.imread(fn)\n", | |
" I = np.array(I, dtype=bool)\n", | |
" return I\n", | |
"\n", | |
"\n", | |
"# Load stroke data for a character from text file\n", | |
"#\n", | |
"# Input\n", | |
"# fn : filename\n", | |
"#\n", | |
"# Output\n", | |
"# motor : list of strokes (each is a [n x 3] numpy array)\n", | |
"# first two columns are coordinates\n", | |
"#\t the last column is the timing data (in milliseconds)\n", | |
"def load_motor(fn):\n", | |
" motor = []\n", | |
" with open(fn, 'r') as fid:\n", | |
" lines = fid.readlines()\n", | |
" lines = [l.strip() for l in lines]\n", | |
" for myline in lines:\n", | |
" if myline == 'START': # beginning of character\n", | |
" stk = []\n", | |
" elif myline == 'BREAK': # break between strokes\n", | |
" stk = np.array(stk)\n", | |
" motor.append(stk) # add to list of strokes\n", | |
" stk = []\n", | |
" else:\n", | |
" arr = np.fromstring(myline, dtype=float, sep=',')\n", | |
" stk.append(arr)\n", | |
" return motor\n", | |
"\n", | |
"\n", | |
"def space_motor_to_img(pt):\n", | |
" pt[:, 1] = -pt[:, 1]\n", | |
" return pt\n", | |
"\n", | |
"\n", | |
"def space_img_to_motor(pt):\n", | |
" pt[:, 1] = -pt[:, 1]\n", | |
" return\n", | |
"\n", | |
"\n", | |
"for stroke_dir in ['strokes_background', 'strokes_evaluation']:\n", | |
" num_strokes = 0\n", | |
" max_num_strokes = 0\n", | |
" num_valid_strokes = 0 # valid data needs to have more than one stroke and the length of each stroke should be more than 20 steps\n", | |
" stroke_lengths = []\n", | |
" train_valid_fnames = []\n", | |
" test_valid_fnames = []\n", | |
"\n", | |
" alphabet_names = [a for a in os.listdir(stroke_dir) if a[0] != '.'] # get folder names\n", | |
"\n", | |
" for alpha_name in alphabet_names: # for each alphabet\n", | |
"\n", | |
" char_dirs = sorted(os.listdir(os.path.join(stroke_dir, alpha_name)))\n", | |
" for char_dir in char_dirs:\n", | |
" if \"char\" not in char_dir: # protect against useless folders, .DS_STORE\n", | |
" continue\n", | |
"\n", | |
" char_renditions = os.listdir(os.path.join(stroke_dir, alpha_name, char_dir))\n", | |
" valid_data = []\n", | |
" for char_rendition in char_renditions:\n", | |
" fname_stroke = os.path.join(stroke_dir, alpha_name, char_dir, char_rendition)\n", | |
" strokes = load_motor(fname_stroke)\n", | |
" num_strokes += 1\n", | |
"\n", | |
" if len(strokes) > 1:\n", | |
" valid_strokes = True\n", | |
" for stroke in strokes:\n", | |
" if len(stroke) < 10 or len(stroke) > 100:\n", | |
" valid_strokes = False\n", | |
" break\n", | |
"\n", | |
" if valid_strokes:\n", | |
" num_valid_strokes += 1\n", | |
" if len(strokes) > max_num_strokes:\n", | |
" max_num_strokes = len(strokes)\n", | |
"\n", | |
" for stroke in strokes:\n", | |
" stroke_lengths.append(len(stroke))\n", | |
"\n", | |
" valid_data.append(fname_stroke)\n", | |
"\n", | |
" if len(valid_data) > 0:\n", | |
" if len(valid_data) > 3:\n", | |
" num_train = int(0.75*len(valid_data))\n", | |
" train_valid_fnames += valid_data[:num_train]\n", | |
" test_valid_fnames += valid_data[num_train:]\n", | |
" else:\n", | |
" train_valid_fnames += valid_data\n", | |
"\n", | |
" print(\"Number of points\", num_strokes)\n", | |
" print(\"Number of valid points\", num_valid_strokes)\n", | |
" print(\"Max Number of strokes\", max_num_strokes)\n", | |
"\n", | |
" with open(stroke_dir+'_train.txt', 'w') as f:\n", | |
" for item in train_valid_fnames:\n", | |
" f.write(\"%s\\n\" % item)\n", | |
"\n", | |
" with open(stroke_dir+'_test.txt', 'w') as f:\n", | |
" for item in test_valid_fnames:\n", | |
" f.write(\"%s\\n\" % item)\n" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"text": [ | |
"Number of points 19280\n", | |
"Number of valid points 6019\n", | |
"Max Number of strokes 12\n", | |
"Number of points 13180\n", | |
"Number of valid points 4644\n", | |
"Max Number of strokes 11\n" | |
], | |
"name": "stdout" | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "jl8rVC3x4q0M" | |
}, | |
"source": [ | |
"## Creating a pytorch dataloader" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"id": "Xhfn61kk10cy" | |
}, | |
"source": [ | |
"!pip install -q torch==1.6.0 torchvision==0.7.0 # Model tested with pytorch version 1.6.0" | |
], | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"id": "pdfn8RYUwkNM" | |
}, | |
"source": [ | |
"import os\n", | |
"from torch.utils.data import Dataset\n", | |
"import numpy as np\n", | |
"from scipy import signal\n", | |
"\n", | |
"\n", | |
"class OmniGlotDataset(Dataset):\n", | |
" def __init__(self, dset_path=\".\", in_seq_len=10, entire_seq_len=20, split_name='train'):\n", | |
" self.in_seq_len = in_seq_len\n", | |
"\n", | |
" with open(os.path.join(dset_path, \"strokes_background_{}.txt\".format(split_name)), 'r') as fid:\n", | |
" lines = fid.readlines()\n", | |
" char_fnames = [l.strip() for l in lines]\n", | |
"\n", | |
" with open(os.path.join(dset_path, \"strokes_evaluation_{}.txt\".format(split_name)), 'r') as fid:\n", | |
" lines = fid.readlines()\n", | |
" char_fnames += [l.strip() for l in lines]\n", | |
"\n", | |
" max_num_strokes = 0\n", | |
" self.data = []\n", | |
" self.fnames = []\n", | |
" for char_fname in char_fnames:\n", | |
" self.fnames.append(char_fname)\n", | |
" char_data = self.load_motor(os.path.join(dset_path, char_fname))\n", | |
" new_char_data = []\n", | |
" for i in range(len(char_data)):\n", | |
" new_char_data.append(signal.resample(char_data[i], num=entire_seq_len))\n", | |
" new_char_data[-1][0] = char_data[i][0]\n", | |
"\n", | |
" curr_data = np.array(new_char_data)\n", | |
" curr_data[:, :, 2] = 1.0\n", | |
" curr_data = self.normalize(curr_data)\n", | |
"\n", | |
" if len(curr_data) > max_num_strokes:\n", | |
" max_num_strokes = len(curr_data)\n", | |
" if len(curr_data) < 12:\n", | |
" new_curr_data = np.zeros((12, entire_seq_len, 3))\n", | |
" new_curr_data[:len(curr_data)] = curr_data\n", | |
" self.data.append(new_curr_data)\n", | |
" else:\n", | |
" self.data.append(curr_data)\n", | |
"\n", | |
" def normalize(self, data):\n", | |
" min_x = np.min(data[:, :, 0])\n", | |
" max_x = np.max(data[:, :, 0])\n", | |
" min_y = np.min(data[:, :, 1])\n", | |
" max_y = np.max(data[:, :, 1])\n", | |
"\n", | |
" data[:, :, 0] -= min_x\n", | |
" data[:, :, 0] /= (max_x - min_x)\n", | |
" data[:, :, 0] *= 10.0 # factor for stability\n", | |
"\n", | |
" data[:, :, 1] -= min_y\n", | |
" data[:, :, 1] /= (max_y - min_y)\n", | |
" data[:, :, 1] *= 10.0 # factor for stability\n", | |
" return data\n", | |
"\n", | |
" def load_motor(self, fn):\n", | |
" motor = []\n", | |
" with open(fn, 'r') as fid:\n", | |
" lines = fid.readlines()\n", | |
" lines = [l.strip() for l in lines]\n", | |
" for myline in lines:\n", | |
" if myline == 'START': # beginning of character\n", | |
" stk = []\n", | |
" elif myline == 'BREAK': # break between strokes\n", | |
" stk = np.array(stk)\n", | |
" motor.append(stk) # add to list of strokes\n", | |
" stk = []\n", | |
" else:\n", | |
" arr = np.fromstring(myline, dtype=float, sep=',')\n", | |
" stk.append(arr)\n", | |
" return motor\n", | |
"\n", | |
" def __getitem__(self, idx: int):\n", | |
" data = self.data[idx].transpose((1, 0, 2))\n", | |
" past = data[:self.in_seq_len]\n", | |
" future = data[self.in_seq_len:]\n", | |
" fname = self.fnames[idx]\n", | |
" return past, future, fname\n", | |
"\n", | |
" def __len__(self):\n", | |
" return len(self.data)" | |
], | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/" | |
}, | |
"id": "91iVloE0wwn7", | |
"outputId": "8d0b383e-38a1-4a41-f086-d082c62def34" | |
}, | |
"source": [ | |
"dset = OmniGlotDataset(split_name=\"train\")\n", | |
"past, future, fname = dset[0]\n", | |
"print(past.shape)\n", | |
"print(future.shape)\n", | |
"print(fname)" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"text": [ | |
"Max number of strokes for a character: 12\n", | |
"(10, 12, 3)\n", | |
"(10, 12, 3)\n", | |
"strokes_background/Burmese_(Myanmar)/character01/0770_01.txt\n" | |
], | |
"name": "stdout" | |
} | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "qihb0PM-4kte" | |
}, | |
"source": [ | |
"## Model Code" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"id": "Dwg9kwcatGUk" | |
}, | |
"source": [ | |
"import math\n", | |
"\n", | |
"import numpy as np\n", | |
"import torch\n", | |
"import torch.nn as nn\n", | |
"import torch.nn.functional as F\n", | |
"\n", | |
"\n", | |
"def init(module, weight_init, bias_init, gain=1):\n", | |
" weight_init(module.weight.data, gain=gain)\n", | |
" bias_init(module.bias.data)\n", | |
" return module\n", | |
"\n", | |
"\n", | |
"class PositionalEncoding(nn.Module):\n", | |
" def __init__(self, d_model, dropout=0.1, max_len=20):\n", | |
" super(PositionalEncoding, self).__init__()\n", | |
" self.dropout = nn.Dropout(p=dropout)\n", | |
" pe = torch.zeros(max_len, d_model)\n", | |
" position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)\n", | |
" div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model)) # 10000.0\n", | |
" pe[:, 0::2] = torch.sin(position * div_term)\n", | |
" pe[:, 1::2] = torch.cos(position * div_term)\n", | |
" pe = pe.unsqueeze(0).transpose(0, 1)\n", | |
" self.register_buffer('pe', pe)\n", | |
"\n", | |
" def forward(self, x):\n", | |
" '''\n", | |
" :param x: must be (T, B, H)\n", | |
" :return:\n", | |
" '''\n", | |
" x = x + self.pe[:x.size(0), :]\n", | |
" return self.dropout(x)\n", | |
"\n", | |
"\n", | |
"class OutputModelBVG(nn.Module):\n", | |
" def __init__(self, d_k=64):\n", | |
" super(OutputModelBVG, self).__init__()\n", | |
" init_ = lambda m: init(m, nn.init.orthogonal_, lambda x: nn.init.constant_(x, 0), np.sqrt(2))\n", | |
" self.observation_model = nn.Sequential(\n", | |
" init_(nn.Linear(d_k, d_k)), nn.ReLU(),\n", | |
" init_(nn.Linear(d_k, d_k)), nn.ReLU(),\n", | |
" init_(nn.Linear(d_k, 5))\n", | |
" )\n", | |
" self.min_stdev = 0.05\n", | |
"\n", | |
" def forward(self, agent_latent_state):\n", | |
" pred_obs = self.observation_model(agent_latent_state)\n", | |
" x_mean = pred_obs[:, :, 0]\n", | |
" y_mean = pred_obs[:, :, 1]\n", | |
" x_sigma = F.softplus(pred_obs[:, :, 2]) + self.min_stdev\n", | |
" y_sigma = F.softplus(pred_obs[:, :, 3]) + self.min_stdev\n", | |
" rho = torch.tanh(pred_obs[:, :, 4]) * 0.9 # for stability\n", | |
" return torch.stack([x_mean, y_mean, x_sigma, y_sigma, rho], dim=2)\n", | |
"\n", | |
"\n", | |
"class Encoder(nn.Module):\n", | |
" def __init__(self, M=10, d_k=64, dropout=0.2):\n", | |
" super(Encoder, self).__init__()\n", | |
" self.d_k = d_k\n", | |
" self.M = M\n", | |
"\n", | |
" init_ = lambda m: init(m, nn.init.orthogonal_, lambda x: nn.init.constant_(x, 0), np.sqrt(2))\n", | |
" self.agent_dynamic_encoder = nn.Sequential(init_(nn.Linear(2, self.d_k)))\n", | |
" self.social_attn = nn.MultiheadAttention(self.d_k, num_heads=8, dropout=dropout)\n", | |
"\n", | |
" self.train()\n", | |
"\n", | |
" def process_observations(self, agents):\n", | |
" agent_masks = (1.0 - agents[:, :, :, 2]).type(torch.BoolTensor).to(agents.device)\n", | |
" agents_tensor = agents[:, :, :, :2]\n", | |
" return agents_tensor, agent_masks\n", | |
"\n", | |
" def forward(self, agents):\n", | |
" B = agents.size(0) # batch size\n", | |
" T = agents.size(1) # max sequence length\n", | |
"\n", | |
" agents_tensor, agent_masks = self.process_observations(agents)\n", | |
" social_obs = self.agent_dynamic_encoder(agents_tensor) # (B, T, M, H)\n", | |
" social_obs = social_obs.view(B*T, self.M, -1).transpose(0, 1)\n", | |
"\n", | |
" # Social Context\n", | |
" encoded_obs, attn_weights = self.social_attn(social_obs, social_obs, social_obs, key_padding_mask=agent_masks.view(T*B, -1))\n", | |
" encoded_obs = encoded_obs + social_obs\n", | |
"\n", | |
" encoded_obs = encoded_obs.view(self.M, B, T, self.d_k).permute(2, 1, 0, 3).reshape(T, -1, self.d_k)\n", | |
" time_masks = agent_masks.permute(0, 2, 1).reshape(-1, T)\n", | |
" agent_masks = agent_masks[:, -1] # Agent masks should only be for agents available at the prediction step\n", | |
"\n", | |
" return encoded_obs, time_masks, agent_masks\n", | |
"\n", | |
"\n", | |
"class AutoBot(nn.Module):\n", | |
" def __init__(self, M, d_k=64, num_modes=10):\n", | |
" super(AutoBot, self).__init__()\n", | |
"\n", | |
" init_ = lambda m: init(m, nn.init.orthogonal_, lambda x: nn.init.constant_(x, 0), np.sqrt(2))\n", | |
"\n", | |
" self.M = M\n", | |
" self.d_k = d_k\n", | |
" self.num_modes = num_modes\n", | |
" self.num_heads = 16\n", | |
" self.dropout = 0.2\n", | |
" _hidden = int(10*d_k)\n", | |
"\n", | |
" self.input_encoder = Encoder(M=self.M, d_k=self.d_k, dropout=self.dropout)\n", | |
" self.output_model = OutputModelBVG(d_k=self.d_k)\n", | |
"\n", | |
" tx_encoder_layer = nn.TransformerEncoderLayer(d_model=d_k, nhead=self.num_heads, dropout=self.dropout, dim_feedforward=_hidden)\n", | |
" self.tx_encoder = nn.TransformerEncoder(tx_encoder_layer, num_layers=1)\n", | |
"\n", | |
" tx_decoder_layer = nn.TransformerDecoderLayer(d_model=d_k, nhead=self.num_heads, dropout=self.dropout, dim_feedforward=_hidden)\n", | |
" self.tx_decoder = nn.TransformerDecoder(tx_decoder_layer, num_layers=1)\n", | |
"\n", | |
" social_encoder_layer = nn.TransformerEncoderLayer(d_model=d_k, nhead=self.num_heads, dropout=self.dropout, dim_feedforward=_hidden)\n", | |
" self.social_encoder = nn.TransformerEncoder(social_encoder_layer, num_layers=1)\n", | |
"\n", | |
" self.emb_pos = nn.Sequential(\n", | |
" init_(nn.Linear(2, d_k)), nn.ReLU(),\n", | |
" init_(nn.Linear(d_k, d_k))\n", | |
" )\n", | |
" self.pos_encoder = PositionalEncoding(d_k, dropout=0.0)\n", | |
"\n", | |
" self.emb_intention = nn.Sequential(\n", | |
" init_(nn.Linear(num_modes, d_k))\n", | |
" )\n", | |
" self.emb_posint = nn.Sequential(\n", | |
" init_(nn.Linear(2 * d_k, d_k)), nn.ReLU(),\n", | |
" init_(nn.Linear(d_k, d_k))\n", | |
" )\n", | |
"\n", | |
" self.mode_parameters = nn.Parameter(torch.Tensor(1, num_modes, d_k), requires_grad=True)\n", | |
" self.mode_net = nn.Sequential(\n", | |
" init_(nn.Linear(d_k, d_k)), nn.ReLU(),\n", | |
" init_(nn.Linear(d_k, d_k))\n", | |
" )\n", | |
" nn.init.xavier_uniform_(self.mode_parameters)\n", | |
" self.prob_decoder = nn.TransformerDecoderLayer(d_model=d_k, nhead=self.num_heads, dim_feedforward=_hidden)\n", | |
" self.prob_predictor = init_(nn.Linear(d_k, 1))\n", | |
"\n", | |
" self.train()\n", | |
"\n", | |
" def generate_decoder_mask(self, seq_len, device):\n", | |
" ''' For masking out the subsequent info. '''\n", | |
" subsequent_mask = (torch.triu(torch.ones((seq_len, seq_len), device=device), diagonal=1)).bool()\n", | |
" return subsequent_mask\n", | |
"\n", | |
" def forward(self, input_sets, horizon=12):\n", | |
" B = input_sets.size(0)\n", | |
" input_horizon = input_sets.size(1)\n", | |
"\n", | |
" # Encode all observations\n", | |
" encoded_obs, in_time_masks, agent_masks = self.input_encoder(input_sets)\n", | |
" in_time_masks[:, -1][in_time_masks.sum(-1) == input_horizon] = False # for stability\n", | |
" encoded_obs = self.pos_encoder(encoded_obs)\n", | |
" in_memory = self.tx_encoder(encoded_obs, src_key_padding_mask=in_time_masks)\n", | |
"\n", | |
" # Predict mode probabilities\n", | |
" mode_params_emb = self.mode_parameters.repeat(B, 1, 1).transpose(0, 1)\n", | |
" mode_params_emb = self.mode_net(mode_params_emb)\n", | |
" mode_probs = self.prob_decoder(mode_params_emb, in_memory.view(input_horizon, B, self.M, -1)[:, :, 0]).transpose(0, 1)\n", | |
" mode_probs = F.softmax(self.prob_predictor(mode_probs).squeeze(-1), dim=1)\n", | |
"\n", | |
" # Embed intention vectors with the linear layer.\n", | |
" intentions = torch.eye(self.num_modes).to(device=input_sets.device).unsqueeze(0).repeat(B, 1, 1)\n", | |
" enc_intentions = self.emb_intention(intentions).unsqueeze(1).repeat(1, self.M, 1, 1)\n", | |
" enc_intentions = enc_intentions.view(B * self.M * self.num_modes, self.d_k).unsqueeze(0)\n", | |
"\n", | |
" # Repeat the tensors for the number of modes.\n", | |
" context = in_memory.unsqueeze(2).repeat(1, 1, self.num_modes, 1).view(input_horizon, -1, self.d_k)\n", | |
" in_time_masks = in_time_masks.unsqueeze(1).repeat(1, self.num_modes, 1).view(-1, input_horizon)\n", | |
" agent_masks = agent_masks.unsqueeze(1).repeat(1, self.num_modes, 1) # [B, K, M]\n", | |
"\n", | |
" # Start autoregressive decoding loop\n", | |
" dec_start_emb = context[-1:]\n", | |
" with torch.no_grad():\n", | |
" dec_input_emb = dec_start_emb\n", | |
" for ts in range(horizon-1): # autoregressive rollout\n", | |
" T = len(dec_input_emb)\n", | |
"\n", | |
" # Encode previous observations/predictions, and combine with intentions.\n", | |
" curr_intentions = enc_intentions.repeat(T, 1, 1)\n", | |
" out_emb = torch.cat((dec_input_emb, curr_intentions), dim=-1)\n", | |
" out_emb = self.emb_posint(out_emb)\n", | |
"\n", | |
" # Run through decoder layers.\n", | |
" out_emb = self.pos_encoder(out_emb)\n", | |
" time_masks = self.generate_decoder_mask(seq_len=T, device=input_sets.device)\n", | |
" out_seq = self.tx_decoder(out_emb, context, tgt_mask=time_masks, memory_key_padding_mask=in_time_masks)\n", | |
" \n", | |
" dec_input_emb = torch.cat((dec_start_emb, out_seq), dim=0)\n", | |
"\n", | |
" # Encode previous observations/predictions, and combine with intentions.\n", | |
" curr_intentions = enc_intentions.repeat(horizon, 1, 1)\n", | |
" out_emb = torch.cat((dec_input_emb, curr_intentions), dim=-1)\n", | |
" out_emb = self.emb_posint(out_emb)\n", | |
"\n", | |
" # Run through decoder layers.\n", | |
" out_emb = self.pos_encoder(out_emb)\n", | |
" time_masks = self.generate_decoder_mask(seq_len=horizon, device=input_sets.device)\n", | |
" out_seq = self.tx_decoder(out_emb, context, tgt_mask=time_masks, memory_key_padding_mask=in_time_masks)\n", | |
"\n", | |
" # Socially encode the future\n", | |
" agent_masks = agent_masks.unsqueeze(1).repeat(1, horizon, 1, 1).view(-1, self.M) # [B*T*K, M]\n", | |
" out_seq = out_seq.view(horizon, B, self.M, self.num_modes, -1).permute(2, 1, 0, 3, 4).reshape(self.M, -1, self.d_k)\n", | |
" out_seq = self.social_encoder(out_seq, src_key_padding_mask=agent_masks)\n", | |
" out_seq = out_seq.view(self.M, B, horizon, self.num_modes, -1).permute(2, 1, 0, 3, 4).reshape(horizon, -1, self.d_k)\n", | |
" \n", | |
" out_dists = self.output_model(out_seq)\n", | |
" out_dists = out_dists.view(horizon, B, self.M, self.num_modes, -1).permute(3, 0, 1, 2, 4) # [K, T, B, M, 5]\n", | |
" return out_dists, mode_probs" | |
], | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "5yRdFh2R48_P" | |
}, | |
"source": [ | |
"## Loss Functions\n", | |
"We define some utility functions for calculating the multimodal loss of the generated characters.\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"id": "m7wxpzvpA-fI" | |
}, | |
"source": [ | |
"import torch\n", | |
"from scipy import special\n", | |
"import torch.distributions as D\n", | |
"from torch.distributions import MultivariateNormal\n", | |
"\n", | |
"\n", | |
"def get_BVG_distributions(pred):\n", | |
" B = pred.size(0)\n", | |
" T = pred.size(1)\n", | |
" N = pred.size(2)\n", | |
" mu_x = pred[:, :, :, 0].unsqueeze(3)\n", | |
" mu_y = pred[:, :, :, 1].unsqueeze(3)\n", | |
" sigma_x = pred[:, :, :, 2]\n", | |
" sigma_y = pred[:, :, :, 3]\n", | |
" rho = pred[:, :, :, 4]\n", | |
"\n", | |
" cov = torch.zeros((B, T, N, 2, 2)).to(pred.device)\n", | |
" cov[:, :, :, 0, 0] = sigma_x ** 2\n", | |
" cov[:, :, :, 1, 1] = sigma_y ** 2\n", | |
" cov_val = rho * sigma_x * sigma_y\n", | |
" cov[:, :, :, 0, 1] = cov_val\n", | |
" cov[:, :, :, 1, 0] = cov_val\n", | |
"\n", | |
" biv_gauss_dist = MultivariateNormal(loc=torch.cat((mu_x, mu_y), dim=-1), covariance_matrix=cov)\n", | |
" return biv_gauss_dist\n", | |
"\n", | |
"\n", | |
"def nll_pytorch_dist(pred, data, agents_masks):\n", | |
" biv_gauss_dist = get_BVG_distributions(pred)\n", | |
" num_active_agents_per_timestep = agents_masks.sum(2)\n", | |
" loss = (((-biv_gauss_dist.log_prob(data) * agents_masks).sum(2)) / num_active_agents_per_timestep).sum(1)\n", | |
" return loss\n", | |
"\n", | |
"\n", | |
"def nll_loss_multimodes(pred, agents_data, modes_pred, entropy_weight=1.0, kl_weight=1.0):\n", | |
" gt_agents = agents_data[:, :, :, :2]\n", | |
" modes = len(pred)\n", | |
" nSteps, batch_sz, M, dim = pred[0].shape\n", | |
"\n", | |
" agents_masks = agents_data[:, :, :, 2]\n", | |
"\n", | |
" modes_pred = modes_pred\n", | |
" log_lik = np.zeros((batch_sz, modes))\n", | |
"\n", | |
" with torch.no_grad():\n", | |
" for kk in range(modes):\n", | |
" nll = nll_pytorch_dist(pred[kk].transpose(0, 1), gt_agents, agents_masks)\n", | |
" log_lik[:, kk] = -nll.cpu().numpy()\n", | |
"\n", | |
" priors = modes_pred.detach().cpu().numpy()\n", | |
" \n", | |
" log_posterior_unnorm = log_lik + np.log(priors)\n", | |
" log_posterior = log_posterior_unnorm - special.logsumexp(log_posterior_unnorm, axis=1).reshape((batch_sz, 1))\n", | |
" post_pr = np.exp(log_posterior)\n", | |
"\n", | |
" post_pr = torch.tensor(post_pr).float().to(gt_agents.device)\n", | |
" post_entropy = torch.mean(D.Categorical(post_pr).entropy()).item()\n", | |
"\n", | |
" loss = 0.0\n", | |
" for kk in range(modes):\n", | |
" nll_k = nll_pytorch_dist(pred[kk].transpose(0, 1), gt_agents, agents_masks) * post_pr[:, kk]\n", | |
" loss += nll_k.sum() / float(batch_sz*M)\n", | |
"\n", | |
" kl_loss = torch.nn.KLDivLoss(reduction='batchmean') # type: ignore\n", | |
" loss += kl_weight*kl_loss(torch.log(modes_pred), post_pr)\n", | |
"\n", | |
" entropy_vals = []\n", | |
" for kk in range(modes):\n", | |
" entropy_vals.append(get_BVG_distributions(pred[kk]).entropy())\n", | |
" entropy_loss = torch.mean(torch.stack(entropy_vals).permute(2, 0, 3, 1).sum(3).mean(2).max(1)[0])\n", | |
" loss += entropy_weight*entropy_loss\n", | |
"\n", | |
" return loss, post_entropy\n" | |
], | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "6Qf-IiT8646l" | |
}, | |
"source": [ | |
"## Training Loop\n", | |
"The training loop takes about 45-60 minutes on a single-GPU machine." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"id": "TQU44dSO1vXV" | |
}, | |
"source": [ | |
"import torch\n", | |
"from torch import optim\n", | |
"import torch.nn as nn\n", | |
"\n", | |
"\n", | |
"batch_size = 64\n", | |
"d_k = 128\n", | |
"num_modes = 4\n", | |
"M = 12\n", | |
"learning_rate = 5e-4\n", | |
"adam_epsilon = 1e-4\n", | |
"entropy_weight = 1.0\n", | |
"kl_weight = 1.0\n", | |
"num_epochs = 100\n", | |
"\n", | |
"if torch.cuda.is_available():\n", | |
" device = torch.device(\"cuda\")\n", | |
" torch.cuda.manual_seed(0)\n", | |
"else:\n", | |
" device = torch.device(\"cpu\")\n", | |
"\n", | |
"\n", | |
"# Defining models\n", | |
"autobot_model = AutoBot(M=M, d_k=d_k, num_modes=num_modes).to(device)\n", | |
"optimiser = optim.Adam(autobot_model.parameters(), lr=learning_rate, eps=adam_epsilon)\n", | |
"\n", | |
"# Initialize dataloader\n", | |
"dset = OmniGlotDataset(dset_path=\".\", split_name=\"train\")\n", | |
"print(\"Number of Characters:\", len(dset))\n", | |
"train_loader = torch.utils.data.DataLoader(dset, batch_size=batch_size, shuffle=True, num_workers=2, drop_last=False, pin_memory=True)\n", | |
"\n", | |
"total_steps = 0\n", | |
"losses = []\n", | |
"for train_iter in range(0, num_epochs):\n", | |
" print(\"Epoch:\", train_iter, \"Entropy Weight:\", entropy_weight, \"KL weight:\", kl_weight)\n", | |
" for i, data in enumerate(train_loader):\n", | |
" past, future, _ = data\n", | |
" past = past.float().to(device)\n", | |
" future = future.float().to(device)\n", | |
" pred_obs, mode_probs = autobot_model(past, horizon=future.size(1))\n", | |
" \n", | |
" loss, post_entropy = nll_loss_multimodes(pred_obs, future, mode_probs, entropy_weight=entropy_weight, kl_weight=kl_weight)\n", | |
" sigmas = pred_obs[:, :, :, :, 2:4]\n", | |
" sigma_magnitude = torch.mean(torch.norm(sigmas, dim=-1))\n", | |
"\n", | |
" optimiser.zero_grad()\n", | |
" loss.backward()\n", | |
" nn.utils.clip_grad_norm_(autobot_model.parameters(), 0.5)\n", | |
" optimiser.step()\n", | |
"\n", | |
" losses.append([loss.item()])\n", | |
" if i % 5 == 0:\n", | |
" print(i, \"Obs_Loss\", losses[-1][0], \"Sigma Magnitude\", sigma_magnitude.item())" | |
], | |
"execution_count": null, | |
"outputs": [] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": { | |
"id": "8m8q_EM_7DuV" | |
}, | |
"source": [ | |
"## Testing Learned Model\n", | |
"\n", | |
"This consistutes the results shown in Figures 3 (left), 13-14 of the paper.\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"metadata": { | |
"colab": { | |
"base_uri": "https://localhost:8080/", | |
"height": 1000 | |
}, | |
"id": "myz8KkJ8Y1dd", | |
"outputId": "43e6bb97-b568-4a26-f0d7-95ffe9208d37" | |
}, | |
"source": [ | |
"import os\n", | |
"from matplotlib import pyplot as plt\n", | |
"import matplotlib.image as mpimg\n", | |
"\n", | |
"%matplotlib inline\n", | |
"\n", | |
"autobot_model.eval()\n", | |
"dset = OmniGlotDataset(dset_path=\".\", split_name='test')\n", | |
"test_loader = torch.utils.data.DataLoader(\n", | |
" dset, batch_size=batch_size, shuffle=True, num_workers=12, drop_last=False, pin_memory=True\n", | |
")\n", | |
"pred_colors = ['r', 'y', 'g', 'm']\n", | |
"with torch.no_grad():\n", | |
" for i, data in enumerate(test_loader):\n", | |
" past, future, fname = data\n", | |
" past = past.float().to(device)\n", | |
" future = future.float().to(device)\n", | |
" pred_obs, mode_probs = autobot_model(past, horizon=future.size(1))\n", | |
" img_fname = fname[0].replace(\".txt\", \".png\").replace(\"strokes\", \"images\")\n", | |
" char_image = mpimg.imread(img_fname)\n", | |
"\n", | |
" num_strokes = int(past[0, 0, :, 2].sum())\n", | |
" gt_past = past[0].cpu().numpy()\n", | |
" gt_future = future[0].cpu().numpy()\n", | |
" prediction = pred_obs[:, :, 0].cpu().numpy()\n", | |
"\n", | |
" fig, ax = plt.subplots(nrows=2, ncols=3, figsize=(15,15))\n", | |
" ax[0, 0].imshow(char_image)\n", | |
" ax[0,0].title.set_text('Char Image')\n", | |
" for m in range(num_strokes):\n", | |
" ax[0, 1].plot(gt_past[:, m, 0], gt_past[:, m, 1], color='b')\n", | |
" \n", | |
" for m in range(num_strokes):\n", | |
" ax[0, 1].plot(gt_future[:, m, 0], gt_future[:, m, 1], color='k')\n", | |
" ax[0, 1].axis(xmin=-1, xmax=11, ymin=-1, ymax=11)\n", | |
" ax[0, 1].title.set_text('GT Strokes')\n", | |
" \n", | |
" row = 0\n", | |
" for k in range(num_modes):\n", | |
" col = (k+2) % 3\n", | |
" if (k + 2) % 3 == 0:\n", | |
" row += 1\n", | |
" for m in range(num_strokes):\n", | |
" ax[row, col].plot(gt_past[:, m, 0], gt_past[:, m, 1], color='b')\n", | |
" ax[row, col].plot(prediction[k, :, m, 0], prediction[k, :, m, 1], color=pred_colors[k])\n", | |
" \n", | |
" ax[row, col].axis(xmin=-1, xmax=11, ymin=-1, ymax=11)\n", | |
" ax[row, col].title.set_text('Prediction '+str(k+1))\n", | |
" plt.show()\n", | |
" if i == 5:\n", | |
" break\n" | |
], | |
"execution_count": null, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"text": [ | |
"Max number of strokes for a character: 11\n" | |
], | |
"name": "stdout" | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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KlfDpp/5L2ADatYODDnJVFiPJ9OluyON115WtJ2vkSJfg3XBD6GObP9+tFffzz67Yy+mnQ1ZW6K8rOylpExHxmXHj3JDDnj1hyhR/JmwAxx7rkpr33vM6krJbtgzef3/vVdlKM3Sou4t9/fWQnx+auHJyXLI2YoT73S9fDmec4QoRjB8fmmuKlFdGhuthy8hwCduxx3odUen69nW96uvXex1J2T39NDRqBP36le39jRvDHXfARx/BtGmhi2vSJJecx8TA7Nnw5pvw3XfQuzds3x6668qulLSJiPjI66+7+SEnneTvhA0gOtpVX/zoo8gprz12rLuDfc01ZT8mLs7NGfntN3d8sGVkuLl1//2vq3j3yituuOmkSe4L8iWXaCFd8d6qVa6HrThhO+YYryPat7PPdr3XH37odSRls3Qp/O9/rhpkeeYCXncdtGnjeuaDva6ktXD//XDeedCpk1uq4dBD3c+vvgozZsC55+69YrEEn5I2ERGf+OYbN8eqZ0+3Rk9Ze4K8dPbZrtT39OleR7J/2dnw4osu5rS08h17xhmumts99wT3zn3xkKPFi10P4E037RwWlZDg/h506+Z64cI1p05kd3l5bi5TRgZMner/hA1c5dcWLSJniOSYMe5G2N7K/O9L8bqSv/7q5hgHy/btMHAg3Hmne5wxw/XsFbv4Ynj2WZdoDhgQ/IRR9qSkTQAwxtxjjJngdRwi1dWaNW7dnRYtXI9LJCRs4BLMWrUiY4jkhAn7r8pWGmPgySddgnr33cGJZ/LkXYccnXXWnu+pWdMla4ce6pLNGTOCc22R8rjxRvj2W9e70r2719GUjTFuiOS0ae7frZ9t3ep62M8/H5o2Lf/xvXu7+c93373nUgkVsXq161V980144AE3AmRvlYWvusqNQpg0CS67zPVsSugoaatGjDEXGmPmGWOyjDGrjDGfGGPCMiJdSaFI6QoKXDn/TZvcF/lIWnMnPt71Qn3wgVug26+sdQVIOneueC/BQQe5u+DPPQe//FK5WEaOdMOKSg45Kk1ysuvdOPBAl9jNnl3xa4uU11tvuSqM//63GxYXSc4+2/US+r2Xetw4t85dRW4ogUtQn3rK3ZS6557KxfLjj3Dkka7gyOTJcNtt+y6Kcv31bi7u+PHwr3/tuci5BI+StmrCGHM98BTwANAYaA6MBXqH4Fpa/0+kHG6/HWbOdMnAYYd5HU35nXuuK9SxZo3XkZRuxgw3fOjaayu3vtA997gkavjwin052b4dLrrIFQ8YMGDPIUelqV8fPvvMLZp+2mluWKVIqP3yiysrf+yx8PDDXkdTft27u2GSOTleR1K6oiKXFB91lNsq6pBDXIGlsWNdW1cRU6a4m1pFRfD11y7pLYs77oBbbnH/h914oxK3kLHWaqviG5AMZAHn7eM99wDvAK8DW4FFQJcS+28F/gjs+xXoW2LfJcA3wJPABuD+Us4/ocTPFrgGWBI4531AG2A2sCUQS1zgvXWBj4B1wKbA82YlztUK+Cpwns+BMbtdq1vgvJnAj8DxXv9OtEXGdsQRR9hQmzzZWrD2qqtCfqlq7Z//tLZRI2u3b6/8uUaNcr+z998v33GrV1vbrZs7duRIa4uKyn/t5cutbdHC2nr1rP355/IfLw4wz/qgjanMFur2afNma9u2tbZJE2szMkJ6qWrt449dm/DGG5U/19q11iYnW3vqqeVrX4qKrH34YWuNsbZr14r9vouKrB061H2WO+8s//Hi7Ktt8rzR0Rb6DegFFAAx+3jPPcB24HQgGngQ+K7E/vOAFFzvbD8gG2ga2HdJ4PzDgBggsZTz7560fQDUBg4GcoHpQOtAkvkrMCjw3vrAOUASUAv4L/B+iXN9CzwGxAHHBpK+CYF9qYFE8vRA7CcHfm7o9e9Fm/+3UH8p+u03a2vVsvbII4OTTMjeLV3qvowE64tEXp61HTpY26ZN2X9vCxdam5ZmbWKitZMmVe76S5dam5JibePG1v7+e+XOVV0padu3oiJrzz7b2uhoa7/6KmSXEWttr17WNm1qbW5ucM73xBPWgrUffVS292/fbu0ll7hj+vWzNien4tcuLLT20kvduR56qOLnqc721TZpGFv1UB9Yb63dX22fWdbajwGMMeOB4cU7rLX/LfG+t40xtwFH4hIvgAxr7TOB52WtIfSItXYLsMgY8wswzVr7Z+D6nwCHA+OstRuAHQWvjTEjgS8Cz5sDXYGe1to8YJYxZkqJawwEPi7+XMBnxph5uCRuXBnjFAm67GxXjS0uzhUeKU+J56rCWsuWLVtYvXo1a9asYc2aNTueb968maZNm5KWlkZaWhrNmzcnNTWV+Ar8QRVXZbvqquDEHRvripL06uXmyd10077fP2WKW8i7Th2YNcvNq6uMNm3g88/dMgE9e7phTC1bVu6cIiU99piruvj44/5cPLuq+P13t3zCiBHu/4Jg+Ne/4Pnn3Vyzk0/e93nXrXNDIGfNckO/77qrcsPHo6Jchd5t2+DWW92SNcOGVfx8sislbdXDBqCBMSZmP4nb6hLPc4CE4mOMMRcD1wMtA/trAg1KvH9FBeIqOQNm215+bgJgjEnCDb3shRsqCVDLGBON6/3baK0tOWJ9BVBc0LsFcJ4x5p8l9scSSPpEvGAtXHmlm3cwdSo0b+51RKH14osvsnz58l2SsuLnuXtZ4C06OpqaNWuyefPmPfY1adJkl0Su+PH444+nQYMGe7x/61Z4+WVXlS0lJXif6dRTXQGW++5zpa/3Ni/NWnj0Uffl5YgjXLGWYMXQoYOb43b88S5x++orN99NpLK++ML9nT33XFd8RELnmWdcUjV4cPDOGRcHTzzh2qcxY0r/HS5aBGee6SpFTpxY9gW99yc62lWb3LbNzSGuUcNVlpTKU9JWPXyLG37YB5hU3oONMS2AF4GewLfW2kJjzEKg5P2YUE47vQFoBxxlrV1tjOkE/BC4/iqgnjEmqUTiVnIFphXAeGvtlSGMT6RcxoxxFdnuv9/dCa3qRo4cyfLly2nUqBGNGzemcePGtGvXjsaNG9OkSZM9HuvXr09UVBQ5OTmkp6ezfPlyVqxYwYoVK3Y8X7x4MVOnTiU7OxuA888/n7fffnuPa7/+euWqsu3L449Dx45uEv6LL+66LzfX9ey99ppLGF99NfgLpR92mLtLf9JJbvvyS2jUKLjXkOolI8NVsm3b1pWgr0yvi+zb5s2ufejfv2zFiMrj9NPdSIB773VrrDVsuOv+Tz5xSVqNGq7dOPLI4F4/NhbefttVu73iCreEzQUXBPca1ZGStmrAWrvZGHMXMMYYUwBMA/KBk4ATrLU37+cUNXBJ2ToAY8ylQMcQhry7Wriet0xjTD1gxypJ1tq/A8Md7zHG3AEcAfwT+DDwlgnAXGPMqbgiJbG4wiRLrbXpYfwMIjvce6/7kn3bbV5HEh4LFiwgOTmZ6Ojoch2XlJRE27Ztadu27V73W2vJzMxk0KBBzJ07d4/9xVXZjjyyclXZStOunRv689RTcM01rkoduCFH55zjhi3efbfbQvXl96ij3OK2vXq5xb9nzIB69UJzLan6nnvOLR7/xRdu/UUJnVdfdcPkQ3FDCVxv2yGHuMWxixfdthaefhpuuMHd9JkyBZo1C8314+Pd+p2nneYq5iYmQp8+oblWdaGS/9WEtfZx3PDGO3DJ1wpgKPB+GY79FXgc12O3BjgEVy0yXJ4CEoH1wHfAp7vtHwAcTaByJfA2rmcRa+0K3LIGt7Pzc9+E/u6LRzZudF+KevVy4/+rg3r16pU7YSsLYwx169bl6KOP5q+//iIzM3OX/dOmuTkj110X9EvvcNddrhx/8RIAixa5RGruXNebes89oe+t6NED3n8fFi92idusWSq5LRXzf/8HrVq5NQkldAoL3Q2lY45xQ6dDoUMHN7/txRfhp5/cenVDhrjhkn36uJtKoUrYiiUlwUcfuc/Yr5/7zFlZob1mlVZahRJt2iJ1wyVt93odh7bI30JRnW3OHFuhcvFSuo8//tgC9ssvv9zl9dNOC25VttI8+6z7nQ4f7qqBNmli7fffh/aaezNlirV16rhYOnWy9uWXK1cJripD1SP36ogjXLl4Ca0pU9y/07ffDu11Nmxwy4P84x/WHn+8u+btt7sqj+G0caOLAdySBMOHW7tkSXhjiBT7apuqyX1eqcqMMV2NMW2MMVHGmF64nrX99iCKeGHpUvd4wAHexlGVHB4Yl7hw4cIdr23f7oYpXn118KqyleaKK9wwpKeecr/XuXODP0ekLP75T0hPd5Xj8vPh8sshLc0Nw12+PPzxSGSx1rVPaptCb8kS9+fct29or1OvnqtM+fXXMHs2jB8PI0eGf5RH3bpu7tzs2W6+3ejRbt7kGWe4YlxFReGNJ1IpaZOqoAkwE7eA+CjgamvtD55GJFKK4qStdWtv46hKiouYlEzaEhJgzhxXBS/UYmJgwgS4/fbwDDnalxo1XCW6n39289t69IBHHnFD3s45B2bO1NBJ2bsNG1xxDCVtoXf99a56cGxs6K81ZIib1/bll64oiVeMgaOPhjffhL//djHNn++mCnTo4IZObtniXXyRQEmbRDxr7YfW2jRrbZK1tq219lWvYxIpzdKl7kt9YqLXkVQtnTp14ocfdr1XY0x4vhQBHHqou4Ndo0Z4rrc/xsAJJ7i1tv78060lN3Ome+2ww+CFFyAnZ7+nkWpEowDCK1xtU0yM623r1i081yuLlBRXkGv5cnfDq25dV5AlNdUVd/r9d68j9KeQJG3GmF7GmN+NMUuNMWG4zykiEhk0/Cg0OnXqxKJFi8jLy/M6FN9p0QIeesgNnXz5ZbeO0pAh7ubBTTfBX395HaH4gZI2Cbe4OBgwAL77zo2M6NvX3VBq3971wP3vfxo6WVLQk7bAgsdjgNOAg4ALjDGqQyQigpK2UOnUqRP5+fksXrzY61B8KzHRLXK7YIEbxnnSSfDkk9CmDZx3Hmza5HWE4qU//nA9tK1aeR2JVEddu7p1NZcvh/vuc0O8zzzTzX2bOtXr6PwhFOu0HYlbA+tPAGPMRFxhiF9LO6BBvWjbMi1M/cQiEhbLVuSzfmOhlmYtYcsWWLtWSVsodOrUCXDFSA477DCPo/E3Y+DYY92Wng7PPguPPeaWDPj0U2/n5Il3li6F5s3d+loiXmncGO64A265xa3zNmKES95efhkuvtjr6LwViqQtFbcWVrF0YI9lTY0xg4HBAM1TY5gzNS0EoYiIV448dcX+31TN/PGHe1TSFnwHHnggSUlJ/Pjjj16HElGaNXNz8Xr2dGs3de/u7mp36OB1ZBJuGgUgfhIbC+ef74ZJnn02DBoEa9bAjTeGfu1Lv/KsEIm19gVrbRdrbZeG9YO/6KqIiN9ozkjoREdHk5SUxPbt270OJSKdeCJ89ZVbKuCYY1xpbqlelLSJH9Wu7ea29e8PN98MN9xQfee5hSJpWwmU7DZrFnhNRKRaK07a2rTxNo6qKicnh6SkJK/DiFidOrlkrUEDN9/tww+9jkjCJTMT1q9X0ib+FB8Pb7wBw4e7ebgDB0J1rDkViqRtLnCgMaaVMSYO6A9MCcF1REQiytKl0KQJ1KzpdSRVj7VWSVsQtGoF33wDHTu6Sm4vv+x1RBIOGrotfhcVBU88AQ8/DG+95Rbm3rrV66jCK+hJm7W2ABgKTAUWA+9YaxcF+zoiIpFmxQpI0/TdkCgeFlnDLwulRbCGDd3C3CedBFdc4ea8aUHuqm1FYAqy2ifxM2PcEMnXXoMvvoDjj3fz3KqLkMxps9Z+HFjkuI21dmQoriEiEmnq1YONG72OomrKzs4GUE9bkNSs6YZHXnSRq+Q2bBgUFnodlYRKvXruUe2TRIJBg1z79NtvrnhS8dSDqs6zQiQiItVNaiqsXKlei1DIyckBlLQFU2ysu6N9000wZowrBKA6L1VTaqp7XKkKBBIhTjvNjQjYvNkVT5o/3+uIQk9Jm4hImKSmui+9mZleR1L1KGkLjagoeOQRN5dk0iRXfnvzZq+jkmBLSXGPStokkhx1lJuDm5johkp+9pnXEYWWkjYRkTDR3ezQUdIWWv/+t6veNns29OgBGRleRyTBlLKhcvUAACAASURBVJjohkiqbZJI066da5dat3bFSd56y+uIQkdJm4hImChpC53iOW0qRBI6F17o1kv68083j+T//s/riCSYiodvi0SalBT48kvXLl14ITz1lNcRhYaSNhGRMFHSFjrqaQuPk0+GmTMhJwfOPdctxi1Vg5I2iWR16sCnn8LZZ7uRAV984XVEwaekTUQkTDRvJHSUtIXPEUfASy/Bzz+7hW6lakhJ0bBXiWwJCTBhghsqedVVVa9wkpI2EZEwiY+HBg2UtIWCkrbwOusst/j2PffAX395HY0EQ2qqW/OqoMDrSEQqLjERnn3WDd9+6CGvowkuJW0iImGkIUihUZy0aU5b+IwaBdHRcPXVWsaiKkhNhaIiWL3a60hEKueUU9zctgcfdGu5VRVK2kREwig1VUOQQmHNmjWAetrCqVkzGDkSpk6Fd97xOhqpLM25larkiScgKckNk6wqN5WUtImIhJF62oJv0qRJjBgxgqOOOork5GSvw6lW/vUvN8ftuuu0/mCkU9ImVUnjxm6NyS+/hHHjvI4mOJS0iYiEUWoqrF2rqnvB8tprr9GvXz+OPPJIpk6dSlSU/lsLp+hoeOEFWLcObrvN62ikMpS0BdGCBVWneyeCXX45HHMM3HgjrF/vdTSVp//dRETCKDXV/V/+3XdeRxL5Ro8ezaWXXsqJJ57I1KlT1cvmkc6dXU/bc8/Bt996HY1UVIMGEBvrfofKNyrhs89c9/Mbb3gdSbUXFQXPPw+bN7vELdIpaRMRCaPTT4fmzaFXL3jvPa+jiVwPPvggw4YNo3fv3nz44YcqQOKxESMgLQ0GD1YvcqSKinLzf956yxVx2LbN64gi1IknulWer70WVq3yOppq7+CD4eab3RDJSF+7TUmbiEgYpaTA99/DIYe4RUAfflh3tcvDWsttt93G7bffzoABA/jvf/9LQkKC12FVezVrwujR8MsvrgCARKann3Zl0idOhBNOUCXJComOhldfdVnvkCFq4H3gjjuqxtptStpERMKsSRN3x69/f7j1Vrj0UsjN9Toq/ysqKmLYsGE89NBDDBkyhNdff53Y2Fivw5KA4rXb7r0X/vzT62ikIoyBW26Bd991i6cfeST89JPXUUWgtm3hgQfgww9h/Hivo6n2qsrabUraREQ8kJgIb77pFiceNw5OPrlqTJQOlYKCAi699FLGjBnDjTfeyLPPPquiIz5UvHbbNdeogyGS9e0LX38NhYVupN+HH3odUQS69lpXBeO662DDBq+jqfaqwtpt+h9PRMQjxsDdd7s5JHPmwFFHweLFXkflP7m5ufTv35/XX3+dESNG8Mgjj2CM8Tos2Qut3VZ1dO7s2qX27aF3bzfsVYl4OURHu2EV+fn6g/OJSF+7TUmbiIjH+veHmTMhOxuOPhqmTfM6In9Yu3YtI0eO5IADDmDy5Mk8+eST3HnnnUrYfE5rt1Udqanw1Vdu/u0NN7hCM3l5XkcVIWbNgsmTXRWMBg28jkaI/LXblLSJiPhAt27urnaLFq7C5NixXkfkDWst33//PRdddBFpaWnccccddOjQgU8//ZThw4d7HZ6UgdZuq1qSklyv6e23w0svucq3Gzd6HZXPFRW5LDclxT2Kb0Ty2m1K2kREfKJ5c3dz9rTTXG/FsGFQUOB1VOGxbds2XnvtNbp27Uq3bt344IMPGDJkCIsXL2batGmceuqpXoco5aC126qWqCg37PX11+Gbb9xNpv/7P6+j8rG333Z34UaOBC1H4iuRvHabkjYRqVaMMf82xiwyxvxijHnLGOOrevG1asH777ubs6NHw5lnuv9cqqply5Zx6623kpaWxqWXXsq2bdsYO3YsK1euZNSoUbRv397rEKWCtHZb+fi9bQK46CKYPh02bXJzcKdP9zoiH0pPd2WBO3WCiy/2OhrZi0hdu01Jm4hUG8aYVOBaoIu1tiMQDfT3Nqo9RUfDY4/Biy+6L0Xdu1et9ZKstXz22Wf07t2bNm3a8Nhjj3HccccxY8YMfvnlF66++mpq1arldZhSSSXXbhs1yuto/C1S2iaAY491nUgpKW6o5IQJpbwxEis9VEZhofsLf9BBbmzwM8+4bh3xpZJrtxUWeh1N2ehvk4hUNzFAojEmBkgCMjyOp1RXXOGKknTsCPXrex1N5RQVFbF+/XqeeeYZOnTowCmnnMK3337Lbbfdxl9//cXkyZM54YQTVGSkijnrLDjxRHjqqeoz1LcSIqZtatUKZs92v98OHXbbaa0bKjBsmCexeeLnn102O2yYGzv6yy/uZ/GtxER4+GE3zDdSlrSI8ToAEZFwsdauNMY8BiwHtgHTrLW71Go0xgwGBgM0b948/EHu5oQT3FZWGzduJDc3l7y8vB2P+3uen59PTEwM8fHxxMXFERcXt+P57o9xcXFs27aNTZs2kZmZueNxf883b95MUVERAEcddRTjx4/nvPPOIz4+PkR/cuIX114LffrABx/AOed4HY0/laVtAn+1T8nJrjjiHoxxPUxjxsDhh7vKD1XVtm1w//2uJGGdOq7b8cIL3Z+B+F6fPm4I9+jR7rnfKWkTkWrDGFMX6A20AjKB/xpjBlprdwzwsda+ALwA0KVLl4gb39OiRQuysrI8uXZiYiJ169alTp061KlTh6ZNm9KhQ4ddXuvRowddu3b1JD7xxplnuqqoo0craStNWdomiKD26cEH4ccf3SrrBx3k1jKpambMgCFDYOlSGDTIjWlXaf+IEhMDV1/tKqMuXryXXmOfUdImItXJScBf1tp1AMaYd4HuQGmzMiLOY489hrV2n71muz+PjY2loKBgj5640nrsEhMTqVOnzo5krG7duiQnJ6vXTPYqOtp9d7/lFjdqrGNHryPyparVNsXEwMSJ0LWry9TnzXOT4KqCDRvgppvg1VehTRv4/HPo2dPrqKSCrrgC7rnHdQyPHu11NPumpE1EqpPlQDdjTBJuCFJPYJ63IQXXkCFDvA5BZA+XXw533+2+GD37rNfR+FLVa5vq1XOlcI8+2iVuM2dCJN/Yyc+Ht95ydeI3bnQVIu+6y02OkojVsCH07+8qST7wANSu7XVEpVMhEhGpNqy13wOTgAXAz7g28AVPgxKpBurXhwsucOt8ZWZ6HY3/VNm26ZBD3Lfh775z3a2RWFFyyRLXTdysmRsG2aoVLFjghoAqYasShg6FrCz3V9XPlLSJSLVirb3bWtveWtvRWnuRtTbX65hEqoOhQyEnB157zetI/KnKtk3nnAP/+Q+88gqMHet1NGWzfTu8+aarAtW2LTz+uOsx/OgjVzbz0EO9jlCCqGtXt+7g6NEQqJflS0raREREJOQ6d3ZrDo4Z4+8vRhICI0a4ijTDh8OXX3odTekWLXIxpqbCgAHw998wciQsX+6Gep5xhpukKVXO0KGu/L+fF4xX0iYiIiJhMXSoK7Y3bY9i9lKlRUW5cvht2sB557kkyA+sdUMd773X3VXo2NH1Bp50Enz2mfvLevvtVaeIipTqvPPc/LZnnvE6ktKpEImIiIiExTnnQJMmbhhSr15eRyNhlZzsequOOgr69oXrr4dNm9wkx02b9twAOnVyY9e6dIHDDgvOHLLcXPjiC5gyxa2qnJ7u1lU7+mg3DPKii9y3d6lW4uNh8GBXjOSvv9zURb9R0iYiIiJhERfnlrYaMQL++MN1vEg10r49vPEG9O4NAwfufD0pCerW3bm1bOmqNX76qateA24ZgY4dXQJXvB1yiPtLVZq8PNi82SWB337rkrSpU13ViaQkOPVUuO8+OP10aNQopB9d/O+qq+Chh1yF20ce8TqaPSlpExERkbAZPNhNExo71nVsSDVz5plurlh2tkvQ6tQpPfGy1vWEzZvntrlzYfJkeOkltz8uzvXAtW4NW7e6XruSW07OrudLSXHJ4llnuSIjCQmh/awSUZo1c53AL73k1m5LSvI6ol0paRMREZGwSUlxwyRfecX1uNWo4XVEEnbNmpXtfcZAWprb+vZ1r1nrxq8VJ3Hz5sH8+W74ZZ060LSpe9x969DBzVszJnSfSyLe0KEwaZJbku/yy72OZldK2kRERCSshg6Ft992VdWvvNLraCSiGON61lq3hvPP9zoaqWJ69HCjcEePhssu81eOr+qRIiIiElbHHONqTIweHZnrLYtI1WQMDBsGCxe6Jfn8pMJJmzEmzRjzhTHmV2PMImPMdYHX6xljPjPGLAk81g1euCIiIhLpjHG9bT/9BLNmeR2NiMhOAwa40bajR3sdya4q09NWANxgrT0I6Ab8yxhzEHArMN1aeyAwPfCziIiIyA4XXODqUPh5XSQRqX5q1HBDIydNgowMr6PZqcJJm7V2lbV2QeD5VmAxkAr0BsYF3jYO6FPZIEVERKRqSUpyE/3ffRdWrfI6GhGRna65BgoLdxYq9YOgzGkzxrQEDge+Bxpba4ub39VA42BcQ0RERKqWK65wX4wmTvQ6EhGRnQ44wK0KMX68f+bdVjppM8bUBCYDw621W0rus9ZaYK8f1Rgz2Bgzzxgzb92GwsqGISIiIhGmXTvo2hUmTPA6EhGRXQ0cCEuXwpw5XkfiVCppM8bE4hK2N6y17wZeXmOMaRrY3xRYu7djrbUvWGu7WGu7NKwfXZkwREREJEINHAgLFsCvv3odiYjITmef7dZf98tNpQqv02aMMcDLwGJr7RMldk0BBgEPBR4/qFSEES7fFvLohoN4b/lhIb1OXEwB17Wezvk1N4f0OiIiIsHUrx9cfz288QaMHOl1NCIiTnIynHWWG779xBMQG+ttPJVZXPsY4CLgZ2PMwsBrt+OStXeMMZcDfwPVeuXDXJvPyzNOoP3j6VBUFLLr2Dq1ePCB0zi/qyYGiIhI5GjcGE4+2SVt990HUVpBVkR8YuBAeOcdmDYNzjjD21gqnLRZa2cBpa0T3rOi560qsoq2M3t7LZbkpZGUEUVB+sqQzmSMzk4mc2U7Xm/XgLZxa+gab4g2+p9PRET8b+BAt33zDfzjH15HIyLinHoq1K/vhkhGbNIm+zZ7ey2Gj7uShj8UkPZ/aygMcemZoqxs2r2czUtTz2ZFL5h9xhM0jakZ0muKiIgEQ58+bm2kCROUtImIf8TFuSHcr7wCW7ZA7drexaKkLcjybSG5Np8leWk0/KGAhI/mEI7amLagAOYvInE+1G7dnTW9YkmOyiPexASlx63QFrHN5gUh0rJLNHHqLRQRqQZq1IC+fd0wpFGjID7e64hERJyBA2HsWHjvPRg0yLs4lLQF2RMb2/PC9J4kZUS5HjYPYmg8J4cLxv2b7c3yePb48fRKyq30OcdvbcKI6X2J2RyeJCq/fgFPnvgWfWpkheV6IiLirYEDXU/bxx+7BE5ExA+6dYPWrV37pKStCnlvxWG0fzydgvSVIR8SWRrzzUKazzbY7ofx1RHt6JX0U6XP+dG6Q2k/ZhOFi5cEIcL9M106Mq1zR/rU+C4s1xMREW/17OmKkkyYoKRNRPzDGBgwwFW3zciAlBRv4lDSFgT5tpBnNh3IJ2sOZuPChtTL+d375dOtJWZjNm/NO4q5rVtU+nR//pxK+y0rwva5ojZl8cm8Q+m1tT6XpM6mf61NYbmuiIh4IyYGLrjADUPatAnq1vU6IhERZ8AAV9124kS3RIkXlLQFweai7Tz78am0fW4VB2T/QeFGfyQYRUv/5qB7siE+rtLnar9tGQVr1gUhqrIpWraCg+7PxSbX5I7/9OG841/W/DYRkSpu4EB46imYNAmuvNLraEREnHbtoGtXNxJASVsEyirazo95cfyW24akVYaCP5d5HdIubH4eBSszvA6jQmxBAQUrM4jakAAZh/NhTm2icOvc1YjKpXPcVupGJ3kcpYiIBFPnztC+vftipKRNRPxk4EC47jpYtAgOPjj811fSVgmfb2vA7a9fTL3FhaQuWudJ0ZGqrig3lwMmbuGReQN3vJbTOIq+l8/k7oa/ehiZiIgEmzHui9Edd8Dff0OLyo/uFxEJin79XC/bG2/AAw+E//oab1YJy/Ia0OT7PGpM+r78BTqiojExMeXeMKWtZ15FWYudv4hab3+3Y0uZvoHFWU28jkxERELgwgvd45tvehuHiEhJjRvDKae4pK2oKPzXV0+bB6Ib1GdV/3ZsbVW+33j0dkOL/+VgZv8YoshERES81aoVHHMMjB8Pt95a/e5Vioh/DRzoipLMmgU9eoT32kravFC/Lqnn/sXkA6eU67Af8+Cq9GtpODtEcYmIiPjAwIFw9dWwcCEcfrjX0YiIOL17Q40abt6tkrYIMH1bNOPWHsN3f7ek9cbtlLUIfkyzVLYekcrWtBjOqPM18Sa2XNdNMNuxuuWIyd7G9z8fwLlFe47urRu3jasafcERQaiYKSIi3jjvPLj2WvfFSEmbiPhFjRpw9tnwzjswahQkJITv2kraKuA/v/el9v01OHD1ZooyVpc5acs8uhnH3v49PWstonN8JlAjlGFWWYXpGRz0oCWnRr099m1sVpvH747jzVZfeBCZiIgEQ/36cPrpbl7bI49AdLTXEYmIOAMHuuHbH3/sErhwUdJWAVtyEqi3JIOCdWVbtyy6fj1M7VpkpUTTN3k+3RKiqUjCFksReckQ06oFdmsWhes3lPscwRRdJxlTJ7nyEw6sxW7MpHDLlrK9vaCAgr9X7HVfYk5zfl7blK+aQsuYLJrH1KxcbCIi4olBg2DbNli/3hUAEBHxgxNPhKOPhry88F5XSVuImdg4Vl7UnrqnZ3BS/e9oF5sLVGx9sbSYKPr2+5pvTmzNus/bkfb0Aoq2bw9uwGVlDOvOPoi489cQF125xQ6y8+KJfuMgar/5XaXDKlq3gQbPNeKGlKvZftZm5h05rtzDUEVExHt9+7pNRMRPYmJgtgf1JZS0hVqUYUv7AhYc/C7RJoqKJmwANaMSuL/Rz9DoZ1qvugyTEA+5ueU7iS3rYM69KNGjZqKj2XwgLOj4JjWjKjegd1VBFie1vJnaxlQuPqAoO5u4qfOoZwx/te3G9q4FxBAd+LMXEREREYk8Stoi1OkdFjH1ts5EFZTvuDq/Qb13f6IoO7tcx0Uf3I7l/6xPfq2dSdUB3f4m1lR+okGtqBjqH7eKZTW6UXexpe57P5c7vr1pPLeITsnX0aB5Jq93fI0OcRVPmEVEREREvKKkLUI9mTKbnAEzy33cP+ZdRtTntcqdFG0+qA63Xfo2Z9ZI3/FagokJytDDmlEJfNbxHbYfXMAxc66g/uc1K5+0WUuNKfNp/3EMW/55GD/en0qHuE2VjlVEREREJNyUtEWoWBNNskks93HxMYUQVfahgtEdDiS7TV02HBJFm9i1JEeV/5plisvEEm9iad9wDek9D6DGqmbE/7SsUsVWbEEBtqCApLV5PL7kZOY2XcqF9b7TcgAiIiIiElGUtEmpTEwMy85tyLUXfEDruLUcGlcIhLbu8qPN3+f7u9J4Z00XttzdgugvKl8hM2bBUhreksKCZp35/bbGfNT2kyBEKiIiIiISHkrawiAqJ4qFeQXUi8qjeUySJ0Ux0guy2FgUw+asBBoVbi7zcbn1irg0eVlgGGToe6haxdakVewmClnAMyltqJ+asmOf3b6dwo2byl2spGjrVlj0O0mZKSxd24CfWm6nYVQBTbUcgIiIiIhEACVtIWbzC2j9Xi5XLrmOTZ0K+PjUp8NeEGNz0TZOmXMV8TNqk7Isn6LMsidtXume8DcfXL2Epf0a7HgtZ2ELWj+zlMIyro+3u6JNmTQZl8qgmdeTf9Jmvjvy5UpXvhQRERERCTUlbaFWVEjU1z/Q8GuIvfho1pxUkw4UhTWEnKJC+KE2jca6RSXCe/WKaRVbk3daT4fWO187PqEP5pVEqFjORlFODvH/m0sjYHmD7mzvWoj62kRERETE75S0hVHy0hwu++RKEptm8chhkzkjKTQLY4/JTOPpH0+kIN/NP7N5UaT9Us61AXzotKaLeOmqk4jd2gwAUwSN5+YSO31Bpdd3ExERERHxKyVtYWS++4V2PyZg27dk/KjunNFqRkiu8+xvPTjw1o0Ubczc8ZrdnkukpzXD6/3K5QMW7ugpzC6ynJJ8E61nRIEt9DQ2EREREalmxo+Hww+Hjh1DfiklbRWQVjeTrf9oTeLqFGJ+XUZhWeeIFRVSlJ1NzIatzFnakluSOoUkvu1/1MZuWuEKcFQh8SaW+Oid68LlRuVD823knXw48eu3YRb9QdH2svVeJq613LW6JwfXWEm/Wr/RILpGqMIWERERkaomLw8uvhhGjFDS5ldPtPkvM+5rz3/TO5Nwb0vM7B/LdXzhqjW0ezSJH5JDk7S1XbeWwqxKLk4dAeJNLK91e4XZhx7I8z/2oN1/GlG0bHmZjm364d8s/akd33buTJ1hOQyoVfmlBURERESkmsjIcI+pqWG5nJK2Cjg4LpGD4/6mEMOUmicRu/9DdmFzc7G//IYJSXRQ6YGCxhBVsyZRNZKwcf4eVHlMQhTHJPzB3BYt2dwohejNdSnKysbm5+3zuIKVGZiVGdSp1YV1BbUAJW0iIiIiUkbp6e6xWbOwXC78C4aJ78WkNOXPmzvy1+iGDDr2a2JCvKB2MFzR5Cs23pXL4kcOoPCog7wOR0RERESqspUr3aN62sQrNrkmhxy/hEltPg+84v/c/pSkfE7p/A7Tt0Vz+1eDqTPL64hEREREpMpST1vkOCRhBcvOjGb1dd3hyEO8DqfSojscyNpruvPHgPocV2+J1+GERcKqLEZ93otD51zA61sa7P8AEREREZH0dKhZE2rXDsvl1NNWCT0S8vimz+P8XZDIFYnDSJ3jdUSVs7Fzff597Tscn7SMxtHxUO7ZepGn6JcltL+7JjSsz5OPncTFXSd6HZKIiIiI+N3KlW5opAlVlYpdKWmrhFgTTdOYmiSYHHLSCrHdD9uxLyq3gKglKyjcssXDCEsXlZAAB7SksHb8jte2tI7i4PgMmsfU9DCyyqkVtZ2tzQ3J3Q8jNmMTBfurJllUSGHmZqJj48graBSeIEVEREQksqWnh21oJChpC4raUQk8dcp4vut+AIWBEaffrm1F3IMHED1zgcfR7Z1p0Yyl/4mnb/udyxUMTEynXWzRPo7yv4NiC7n5okksOieV/00+muaPrN5vJUkRERERkXJZuRKOPz5sl1PSFgTRJoqzauRwVo2fdrz2RtIKxjY6j9q1au18Y35+mRd/DgpjiEpMhOg9qz8WNKjJKQcs5uHGC3fbkxCe2EKkZlQCl9ReS2Gt1UxK7QpR4emyFhEREZFqorDQrdOmnrbI1zVhOdGXr+H3Mw/c8VrSrwk0f+l3CteHZ02wmFYtWHp5U/LTcvfYV6v2Nm6vNzcscYiIiIiIVBlr10JBgZK2qqBtbA2+OuQ9KFFU8uTUf2LeqQVhStrymyTT5/Rv99KbJlJ9GWPqAC8BHQELXGat/dbbqERkd4MHD2bOnDksXFg9/g9T2yQSQcK8RhsoaQur7g3+ZFK/44jbnBKW62U3s1yW9HdYrhXp7PbtMC+ZzrH9ODntd+5uOIekqDivw5LQeBr41Fp7rjEmDkjyOiAR2VNeXh6ZmZlehxFOaptEIkWY12iDICRtxphoYB6w0lp7pjGmFTARqA/MBy6y1qoSBHBT/fmcP2Qe+TY8y+MlRRXQIiaO6lC6v7KKsrJo8ewizOs1mHJld4ZdNktJWxVkjEkGegCXAATaJrVPIj4UFxdHXl71+OeptkkkwhT3tEVS0gZcBywGileWexh40lo70RjzHHA58GwQrhPxakYlcHBY84D4/b9FHGspzNwMmZtJWtWC1zOPoGPiCv6RsJ660brZWYW0AtYBrxpjDsPdWLrOWptd/AZjzGBgMEDz5s09CVJEqlfSRhnaJlD7JOIb6ekQGwsNGoTtkpXq8jHGNAPOwI3BxhhjgBOBSYG3jAP6VOYaIuHWZFoG027pwZ1jL+HdrNZehyPBFQN0Bp611h4OZAO3lnyDtfYFa20Xa22Xhg0behGjiFDtkrb9tk2g9knEN9LT3Xy2qPCMnoNKJm3AU8DNQPHiXvWBTGttQeDndCB8M/RESoqCqMQETGz5ujcL/vqb+E/m0mhuDsvz6ocoOPFIOpBurf0+8PMk3BclEfGZ2NjY6pS0qW0SiSQrV4a1CAlUImkzxpwJrLXWzq/g8YONMfOMMfPWbSisaBgiexVtojj3yLksfrQtK27sQkxqeIq/iL9Za1cDK4wx7QIv9QR+9TAkESlFcU+btdbrUEJObZNIhElPD+t8NqhcT9sxwFnGmGW4wiMn4iof1THGFM+Vawas3NvBu3Tx199z8WeRynq0yQ8sPf15jjjrF4oaJHsdjvjHMOANY8xPQCfgAY/jEZG9iIuLw1pLYWG1ubGrtkkkEljretoiJWmz1t5mrW1mrW0J9AdmWGsHAF8A5wbeNgj4oNJRilRQtImic+3lrDitLlsu6Eb0Aa28Dkk8Zq1dGLhhdKi1to+1dpPXMYnInuLi3ND2/Px8jyMJD7VNIhEiMxNyciJneOQ+3AJcb4xZipvj9nIIriFSZpcmL2bckKe48I5PWH9ME6/DERGRMihO2qrRvDYRiQQerNEGQVpc21o7E5gZeP4ncGQwzisSDMlRiRwRD7CE1xK8jkZERMpCSZuI+FLxGm1VoKdNREREpFKUtImIL/32m3uMlDltIiIiIqGipE1EfGf7dnjiCejaFdLSwnrpoAyPFBEREQkmJW0i4jtjx8KKFfDaa2BMWC+tnjYRERHxHSVtIuIrmzfDyJFwyilw4olhv7ySNhEREfEdJW0i4iuPPQYbN8KDD3pyeSVtIiIi4jtK2kTEN1avdnPZ+vWDzp09CUFJm4iIiPhObGwsoKRNRHzgvvsgLw/uv9+zEJS0iYiIiO8U97Tl5+d7HImIVGt//AEvvABXXgkHi9pmlwAAIABJREFUHOBZGEraRERExHc0PFJEfOHOOyEuzj16SEmbiIiI+I6SNhHx3A8/wFtvwfDh0LSpp6EoaRMRERHfUdImIp677TaoVw9uvtnrSLS4toiIiPiPkjYR8dQXX8DUqfDoo5Cc7HU06mkTERER/1HSJiKesdb1sjVrBkOHeh0NoJ42ERER8SElbSLimZkz4fvvXdXIhASvowHU0yYiIiI+pKRNRDzz/PNQpw4MHOh1JDsoaRMRERHfUdImIp5YuxbefRcGDYLERK+j2UFJm4iIiPiOkjYR8cSrr0J+PgwZ4nUku1DSJiIiIr4TGxsLQH5+vseRiEi1UVTk5rH16AEdOngdzS6UtImIiIjvGGOIiYlRT5uIhM/nn8Off/qulw2UtImIiIhPxcXFKWkTkfB5/nlo0ADOOcfrSPagpE1ERER8KSoqisLCQq/DEJHqICMDPvgALrkE4uO9jmYPStpERETEd6y15OTkkJSU5HUoIlIdvPIKFBbC4MFeR7JXStpERETEd3JzcykqKqJmzZpehyIiVV1hIbz4IvTsCQce6HU0e6WkTURERHwnKysLgBo1angciYhUeZ9+CsuX+7IASTElbSIiIuI7xUmbetpEJOSefx4aN4bevb2OpFRK2kRERMR3srOzASVtIhJiK1bA//4Hl10GcXFeR1MqJW0iIiLiOxoeKSJh8dJLYC1ceaXXkeyTkjYRERHxHQ2PFJGQW7wYxo6FU06BVq28jmaflLSJiIiI72h4pIiE1MKFcNxxEBMDTz7pdTT7paRNREREfEfDI0UkZL77Dk44ARIS4KuvoEMHryPaLyVtIiIi4jsaHikiITFzJpx8MtSvD19/7dt12XanpE1ERER8R8MjRSToPv0UTjsNmjd3CVuLFl5HVGZK2kRERMR3NDxSRILqvffgrLPcUMiZM6FpU68jKhclbSIiIuI7WVlZxMfHExMT43UoIhLp3ngDzjsPunSBGTOgYUOvIyo3JW0iIiLiO9nZ2RoaKSKV9+KLcNFF0KMHTJsGdep4HVGFKGkTERER38nKytLQSBGpnKeegsGD3Ty2//0PIvhGkJI2ERER8Z2srCz1tIlIxRQWwogR8O9/wznnuPlsiYleR1UpStpERETEdzQ8UkTKrbAQ3n4bDj0U7r7bDYucOBHi4ryOrNIqlbQZY+oYYyYZY34zxiw2xhxtjKlnjPnMGLMk8Fg3WMGKiIhI9aDhkSJSZoWFLjk75BDo39+9NnEivPYaVJFiRpXtaXsa+NRa2x44DFgM3ApMt9YeCEwP/CwiIiJSZhoeKSL7VTJZu+CC/2fvvsOkqu4/jr+/21jYFViKSAcpKvpDxVVQioIiIijYCCpKLCH2EmuImmgSS2xgJBZsBBULIJJYEVssCwIqKCoQVFhgWZC+wLY5vz/ubFxhF7bN3Dszn9fz7DM7d2bu/cwFDvOdc+45kJTk9bQtWgS/+pV3P07U+J2YWSOgH/AkgHOuyDm3CRgGTAo/bRIwvLYhRUREJLEUFBSop01EKlZaClOmwCGH/FysvfQSLFwII0bEVbFWpjbvqCOwDnjazD43syfMLANo4ZxbE35OHtCioheb2Rgzm2dm89b9VFqLGCIiIhJvzIxQKOR3DBEJkvLF2jnneEMfX37ZK9bOOisui7UytXlnKUAP4BHn3OFAAbsMhXTOOcBV9GLn3OPOuWznXHbzpsm1iCEiIiLxJjMzk4KCAr9jiEgQlJbC88/vXqx9+SWceWZcF2tlavMOc4Fc59yc8P2peEXcWjNrCRC+za9dRBEREUk0GRkZKtpEEl1ZsXbwwXDuuZCaClOnJlSxVqbG79Q5lwesNLMDwpuOBxYDM4HR4W2jgVdrlVBEREQSjoo2kQS2a7GWluYVa1984a27lkDFWpnazoF5JfCcmaUBy4EL8ArBl8zsIuBHYEQtjyEiIiIJJiMjgx9//NHvGCISaVu2wOLF8PXXP99++SXk5XnrrU2bBsOHJ2ShVl6tijbn3BdAdgUPHV+b/YqIiEhi0zVtInFmyxb45huvKCv7WbwYVq78+Tnp6XDQQXDCCXDaaSrWyomP1eZEREQkrmh4pEgM+/57eO+9n3vOvv664uLs2GO9IZDdunm3HTpAsiYorIiKNhEREQkcFW0iMcY5eP99GDcO/vUv73754qysMFNxViMq2kRERCRwMjIy2LlzJ6WlpSTrw51I3fr2W8jPh759wax2+9q501s7bdw4b720Zs3glltg1Cjo1EnFWR3RIFERSThmlmxmn5vZv/3OIiIVy8zMBEio3ja1TRI1l17q9X716AHPPQfFxdXfR14e/PGP0K4dXHih17P25JPeMMg77oCuXVWw1SEVbSKSiK4GvvE7hIhULiMjA0isog21TRItubneMMXCQq9HbP/94f77vclC9mb+fDj/fK9Y+/Of4eijYfZsb8bHCy/0hkRKnVPRJiIJxczaAEOAJ/zOIiKVS7SiTW2TRNXatd4MjV99Bf/+N3TuDNdfD23bwo03ekVdeSUl3tT7fftCdja88orXW7dkCbz6KgwYUPthlrJHKtpEJNGMA24EQn4HEZHKJeDwSLVNEh07dsDWrdCihTed/pAh3kyPn30Ggwd7PW4dO8Lo0fDpp979zp3hzDO9Yu6BB7zb8eO97RIVKtpEJGGY2VAg3zk3fw/PGWNm88xs3rp166KYTkTKK+tp27Ztm89JIq8qbVP4eWqfpPbWrvVuW7T45fbsbHjhBVi2DC67zOtZO+YYrweuQwevd23ZMrj2WmjUKOqxE52KNhFJJL2BU83sB+AFYICZPVv+Cc65x51z2c657ObNm/uRUURIuOGRe22bQO2T1JGyom3ffSt+vGNHrxdtxQp44glYsMCbyn/4cE0s4iMVbSKSMJxzv3fOtXHOdQBGAu8650b5HEtEKpBIRZvaJomq/Hzvdteetl01aQIXXQSHHx75TLJXKtpEREQkcBLwmjaR6KhseKQEmhbXDoj/Fm9jyuZsNhY3iOpxk8wxpNGXHFdf1z1LYnHOvQ+873MMEalEIl3TVp7aJom4vQ2PlEBS0RYQ49f1Z/49PchcuSOqxw2lJvPvqw7hq2MmkWzqeBURkWBIpOGRIlG1dq03kYjWU4spKtqiaHuoiLWlRRSz+zoWCze0ptHCnyj9bllUM6Wkp1O4+jCWFO+kcVKIfZMbxF3xVuiKWV1SyNKitiQV+51GRESqQkWbSISsXatethikoi2KHtjQneemDSBt8+6PZa4Owdpvop4pVFRMx1eLGbn8erYcWsRbx4+na2pG1HNE0qQt7bl/+jAyVsJ+czZQ6ncgERHZq+TkZNLT01W0idS1tWt1PVsMUtEWRR+s68L+k1dTsvyHCh/3pZgIlZLy7nz2exfq/fpo8o7LoGuqH0Ei59PNndj/pU2EvvxGBZuISAzJyMhIuGvaRCIuPx+6dfM7hVSTirYIK3aljF2bzatL/o+URZl02LrU70iVavTfnYye9RuyWm7h7m7TObFBbI8lvHP9AUz6picszaDzhpVUdaoVO/L/WNNnH7a1D3Flg+8jmlFERCqXkZGhnjaRurZ2LfTv73cKqSYVbRFW6Ip55d2edL17KW7HTkq3b/c7UqWSP13EQYsyKO3ajn+O682JHd73O1KNlboQE+f0o9utKwgVbKekGt/UrumzD3+/8h90SdlGs+T6gBaSFBHxg4o2kTpWXAwbNmh4ZAxS0RYhm0M7eHVbW77d0YqMVUmU/rQBnPM71h65khJKN20mZf1Wcr7vyJ2Za+iT+R39Ijy5UKkLMWtHfRZs70CogklaarbPJNJXplL600ZccVG1XhtKhQ4p22iZklknWUREpGYyMzNVtInUpbKFtTURScxR0RYhH+3M4t4nR9Dis520+SGXkoAXbOWFVufR5d4GvNOsD09feDSLj32SVItcb9PG0A4uffsSOr1cUqf77bhyDaUlsT3EU0QkkemaNpE6poW1Y5aKtgj5qSSTrCUlJL+/gLotRSIvtHMnfLGYtJQUGHgkK0p20CQpiYZJ6XWyHMD2UBGbQz/3fq0uTSPzhxSS35tb632XV91JR5LS07H0epSmQXwteiAiEpsyMjJYs2aN3zFE4oeKtpilok0q5UpLafd2EcM23sj2Awv513EPc3Ba/Vrv9/o1/XjvtR4kFXr3k0qg5Uf+Dn9Jyshg9W8OpeDIHfTttIjGSfqnISLiN13TJlLHVLTFLH0ylco5R8rs+bSeDVt/1Yv/9m7KwWm1n0hl9vKudPr7t951fgFhDRpQ0nczy45+LrwlwhfyiYjIXqWmprI9wBN4icScsmvaVLTFHBVtMS6ldSt+6t+OnVlVG9DX6PsSGryz0BsCGQVfFBZy0/IzWLN1n/9tS/ssE7ezMCrH35uUNq1Z378dBa2MPm0/9zuOiIiElZSUMGvWLPr06eN3FJH4sXYtNGgAmZpsLdaoaItxhV32o8fVX3B58/eq9PzT5/yWzvMaEcqLTtH2ypYeFN7fkrYLVvxvm9u+itKADHfZ2XU/el49j0ubfUCrFANqP/xTRERqb9asWeTn53Peeef5HUUkfqxdq5kjY5SKtoBIbtgQ16EVLq16fySbutTjiMwfqnytWad917P90LakN8uCH1cR2rq1JnH36pui7XyyY3/eWnUQjddspyRvbUSOU1Mp+7WgtHUzNnVJIzvzew5Ka+B3JBERKWfy5MlkZWUxePBgv6OIxA8z6NjR7xRSAyraAmLnUV0oun4jhzX9vlqv65++gZMzlgFV6+a+s8MrTLm7J++u6krjezqT9J/IDAm88JvzSJnYjIZrC0n67/Jqz+QYaXmn7s/BF3zN8fus4qSMH4EMvyOJiEjY1q1bmTFjBqNHj6ZevXp+xxGJH5Mn+51AakhFW0AUNknlhk5vMzyjJuvRVH1c8mH16nFYiy94pv5qnm40vM6n29geKqLQlZC3KosD3/qKUEGB/wWbGUn16kFS0v/ub2sLD7R5g2bJGahgExEJlunTp7Njxw4NjRQRCVPRJnVmTck2Tpw/huKFjWnzZSmuKBgLWyd1P5Bl5zSmpOnPefoe/DX7JKX5mEpERCozefJk9t9/f44++mi/o4iIBIKKNqkz60IppL7diFaPfAKA8zlPmYKO+3DrsJc5v+H6XR5J9SWPiIhUbtWqVbz77rvceuutmJnfcUREAkFFm9TaF4WF3LFyKEvW70uzFSW12lfyAZ356ajmhOqwntrYzdEpLR+o2rIIIiLin+effx7nHKNGjfI7iohIYKhok1p7ZkNvNv61Pe2/XkNow/eEarGv/D7NGXP9q3Svt7LO8jVKKmT/1FRUtImIBN/kyZPp2bMnXbp08TuKiEhgqGiTGltSXMCiwpZ8vGZ/mq/cQknuqprtyIyUVi0JZTWkoK1xXIOldE2ty8lBNJ2/iEgsWLhwIYsWLeLhhx/2O4qISKCoaJMaKXUhzl10AamTm9Aovwi3cmmN95VUvz7LL+7A4Sd+w8mNP6VNsq41ExFJRJMnTyYlJYVf/epXfkcREQkUFW1SJeZge6ge20ObACimlJ9+zKLrjM9xhYXVGxJphqX8XJhZg/oUd93B8x3fC2/RrI4iIommtLSU559/nsGDB9OsWTO/44iIBIqKNqmShos3ccfks7m1YXhOSAet5oZwxdWfeKSkfw9+HJJKKM3bl0t1nHvwp3UZV0REYsy7777L6tWrGTdunN9RREQCR0WbVEnoq29puzj5lxtdCFz1J/Zfd3g9Xj/zXjqm/Ly0dxKGJgoREUlczz77LA0bNuSUU07xO4qISOCoaJOqC5XW+KWWmkboqG5sbZ/O1oOLaJwEqZa89xeKiEjcKygoYNq0aYwcOZL09PS9v0BEJMHUqmgzs2uBi/HWUV4EXAC0BF4AmgLzgfOcc0W1zCkxLikzg+9+ncoj/Z+mbcommibV9zuSiIgExIwZMygoKOC8887zO4qISCDVeDyambUGrgKynXOHAMnASOAe4EHnXGdgI3BRXQSV2GT16pHSvi2hTq1p3moTJzUo5OC0+iSbhkKKiAg453j88cdp164dffv29TuOiEgg1faTcwpQ38xS8BbDWgMMAKaGH58EDK/lMSSWHdKZb//SjAYPrOWOA2b6nUZERALm5Zdf5sMPP+TGG28kKUlf6ImIVKTGwyOdc6vM7D5gBbADeBtvOOQm51zZlIK5QOuKXm9mY4AxAO1a69K6uGMGlkRh8wZc2WMW12T94HciEREJmC1btnDNNdfQo0cPLrnkEr/jiIgEVo2rJTPLAoYBHYFNwMvASVV9vXPuceBxgOxD06s/BaEEWkn/HuQen0ZJ+50cWX85mhlSRER29ac//Ym8vDxmzJhBcrImpxIRqUxturhOAL53zq0DMLPpQG+gsZmlhHvb2gCrah9TYs2ao+vx+qi/0SalHvUsde8vEBGRhLJw4UIeeughxowZw1FHHeV3HBGRQKtN98cKoJeZNTAzA44HFgPvAWeGnzMaeLV2ERND+vpi/vztyVyxqifzC2Nzsk1LTYNe3dl+ek92dimkWXKyCjYREdlNKBTi0ksvJSsrizvvvNPvOCIigVeba9rmmNlUYAFQAnyON9zxNeAFM/tLeNuTdRE03qV9toQWN+7H1+3+j7tu2Yepnd7xO1K1JTVpzDe/TeWuY17iwLQ8Mq2e35FERCSAJk2axCeffMLTTz9NkyZN/I4jIhJ4tZoBxDn3R+CPu2xeDmicQzWFtm6Fb7bSYGd71u/IjNhxNpZu58eSZBYVtCGpOFT9HSQlk9y0CZa+e0FW2qIx7Vv/xMh9NgIq2EREZHcbNmzgxhtvpHfv3px//vl+xxERiQmatjHB3JrXnw+nHEHGmhBNvl5Jyd5f8gvJzZuy7JpOND0sf7fHGqRu4YYOb9dNUBGJuJkzZ3LFFVeQnJxMUlLS/36qcz85ORkz+8Xje/ope235271ta9asGZdddhnp6el+nzKpA2PHjmXjxo384x//0BT/IiJVpKItwXya1562U5ZTsiav2gUbgGU0oP1Rucw66F91nk1EoqtFixYcf/zxhEKh//2UlpZWer+ix4qKiv533zn3i8d3/Sl7ffnbirbt+lhxcTGvvfYaM2bMYJ999vH7tEktzJkzh8cff5xrr72W7t27+x1HpOrmzIFvv4XRo/1OIglKRVuEHFxvNbmnl5De/RhaflJIyuz5VXqd27KVDW8dSMfciznxkK95uPVHpFrtpkHeHipizIoT+fibzjRcmIYryKv2PpIP6sLKIc3Z0TLEFfu9Was8IhIMPXv2pGfPnn7H2Ktnn32WX//61xx//PG88cYbNG3a1O9IUgOlpaVcdtlltGzZkj/96U9+xxGpnhdfhCeeUNEmvlHRFiGHpaXw+fET2HBcKYNTb6D9uwZu78vRlf60gVYPz8fS0nj3D4exfdS7NLL6tcqyzRUz/+1uHHjvl7iSEkoLC6u9j82HNOG6i6cyLOMHMpPqAVpPR0SiY9SoUTRq1IizzjqLfv368fbbb9O6dWu/Y0k1PfrooyxYsIAXX3xRPaYSe7ZsgYYN/U4hCUxFW4QkWxKNrD6pFFHccSeFg7NJz98Bi5bi9lI0ucJCXFERSaW1y5BfWsCkzd1ZtLU1GbmOUEFBtfeR3LUTO/ZvwoZuyXRJyyMruUHtQolIoDgHRUWwYwds3+7d7tgBWVkQpLrolFNO4c033+TUU0+lT58+vPPOO3Tq1MnvWFJFeXl5/OEPf2DgwIGcddZZfseRGFFaunvbVFgIhx7qQxgVbeIzFW0R1iApjSl9HmfBER24d/6JHDi2OSUrc6Ny7NcLOvLCQyfSfMFWWuQur/Y1bJaSwg9ntWDMOa/TpV4eh6eVAGmRiCoi1RAKwdatsGkTbN7s3Vb2e9ltQcHPH3rKfwDavr3iQQC/+x3cf3/039ueHHfccbz77rucdNJJ9OnTh7feekvXRcWIG264gR07dvDwww/jLe0q8cg52Lmz6u3Spk1eW1ZZ21RcvPsx6tf3Hou6LVtAPcTiIxVtUXBUvVSOqreKaa3WQ2rVT3nyTuO74hQaJ1W/hwxgwbb2ZC0pxM37qnoFmxnJjRpiGRnsaF3CpY2XhhfJVsEm4rdHH4XLL/cKtz1p0AAaNYLGjb3bjAxo1sz7wNOggXdb/vddbw84IDrvp7qys7P5z3/+w8CBAzn22GN5/fXXOfroo/2OFWgbNmzAzMjKyvLl+B988AHPPvsst9xyC127dvUlg0TeTz9Bt26Qv/vk0r+QkvLLtmmffaB584rbocraKF+op018pqItqJyj7axt/Hbj1bgazohcb5Oj2dIfq93DltKqJUsvb096t01c0uk9UnT9mkhgfPGF98Hljju8Dz1lH3x2vU1N9Ttp5Bx00EF8/PHHnHDCCZxwwgnMmDGDgQMH+h0rkH744Qd69+7Nxo0b+fWvf821115Lly5donb8oqIiLrvsMjp27MjYsWOjdlyJvlWrvILtvPPgmGMqbpcaN/aKrpjsbN26FVq29DuFJDAVbUGWs5B9c2q3i5pM6+8aZdK971KmdnonvEXr6IgERXGx98Hnd7/zO4m/2rdvz0cffcSgQYMYMmQIU6ZM4YwzzvA7VqDk5+dz4oknsn37dkaMGMGTTz7Jo48+yrBhw7j++us55phjIj5Ucdy4cSxevJh//etf1K9fu0m1JNjKhjKedRaccoq/WSJCPW3iM30aj6IT9v2WpRe3JP/yY0juqgvoRaT6ioogTSOVAW+duffff58jjzySESNG8NRTT/kdKTC2bt3KySefTG5uLv/+97955pln+PHHH/nDH/7Ahx9+SJ8+fTjmmGOYNm0apaW1nPWqEitWrOD2229n+PDhDB06NCLHkOAoKvJu47Z92r4dtm3zO4UkMBVtUXRNk8V8MOpefnv5q2zp3szvOCISg4qL43voY3U1btyYt99+m4EDB3LRRRfxwAMP+B3Jd4WFhZx22ml88cUXvPzyy/Tu3RuA/fbbjz//+c+sWLGChx9+mPz8fM4880y6du3KhAkTKKjBDMN7cu211+KcY9y4cXW6XwmmsqItbtun886DqVPhtdf8TiIJSkVbFNWzVFqmZNIqdSOh5IAM6DYjuXNHQsceTulxPSg9rgcbDm9C+wYb/E4mIhVQT9vuMjIymDlzJmeddRbXXXcdDz/8sN+RfFNaWsqoUaOYPXs2Tz31FEOGDNntORkZGVx++eUsWbKEadOmse+++3LFFVfQrl07brnlFvLy8mqd4/XXX2f69OncdttttG/fvtb7k+ArGx4Zt+3TnXdC9+5wwQVQB/9GRKpLRVuCs7Q0vh/VkmMemkvf8Tn0HZ/DyLFvckWzD/2OJiIVUE9bxdLS0pgyZQq9evVi4sSJfsfxhXOOK664gqlTp3L//fdz/vnn7/H5ycnJnH766Xz66ad8/PHHHHvssdx55520b9+eiy++mMWLF9cox44dO7jyyis58MAD+V2iX3yZQOK+py09HaZM8SYkueCCvU/hK1LHVLT5IM1KKUk3khs3wurV8yeEGUkZGSRnNWZnuyJua7aIPzZfzB+bL+aarB/omJrpTy4R2SP1tFUuOTmZIUOGsHDhQn766Se/40Td7bffzqOPPspNN91U7WLpmGOOYfr06Xz33XdcfPHFPP/88xx88MEMGTKE9957D1fRYn6VuOeee1i+fDn/+Mc/SNNf1oQR9z1t4K1p8MAD8Oab8NBDfqeRBKOizQfd0n6i2a9/5LuH92fjr3pAUvSn1E9p14blv+/O0nEt+E32f0g2/VUQiQXqaduz/v37A97aYIlkwoQJ3H777Vx44YXcddddNd5Ply5dmDBhAitWrOCOO+7gs88+Y8CAAWRnZzNlyhSKK1rtuJylS5dy9913c8455/zvz0ISQ9z3tJW55BI49VS46Sb48ku/00gC0Sd1H7RLyeT1A15ncf/HWd/DYUnRv76ttElDjjvxC5b0+ydjm30X9eOLSM2op23PjjzySBo0aMB7773nd5SoefHFF7nyyis59dRTeeyxx+pkGv9mzZpx6623smLFCiZOnMj27ds555xz6Ny5Mw8++CBbt27d7TXOOa688krq1avHfffdV+sMElvifvbIMmbw5JPQtCmcfbY3q6RIFGidNh8lkUTbbnmsufIoLDzjcsoOx74frqP0u2W13n9yi33ZcML+7Gy6e22+o4XjrH2+r/UxRCS6iopgn338ThFcaWlp9OnTJ2GKtlmzZnHeeefRp08fXnjhBVJS6va/9fT0dC6++GIuvPBCXn/9de677z5+97vfcfvttzNmzBiuuuoq2rRpA8D06dN56623eOihh2ipRYgTTkIMjyzTrBlMmgQnngjXXw//+IffiSQBqGjzUaol88pBz7PugJ+vFfjP9k5M3DGcRnVQtJW2b0Hny7/ltta7T0+biqNVSj0g3scxiMQXDY/cu+OOO46xY8eSn5/Pvvvu63eciPnss8847bTTOOigg5g5c2ZEF69OSkpi6NChDB06lHnz5nH//ffzwAMP8OCDD3L22WdzySWXcPXVV3P44Ydz6aWXRiyHBFfCDI8sM3CgV7Dddx8MGgTDhvmdSOKcijafZSU3IKvcJW1b01ewpUMSjY/8v1rve8NBmQxquIKuqRm13pdIPDCztsA/gRaAAx53zo33N1X1aHjk3pVdS/X+++8zYsQIn9NExrfffsvgwYNp3rw5b775Jo0bN47ascuub7vrrrsYP348EydOZPLkyQBMnTq1znv7EkE8tE0J1dNW5q9/hdmz4aKL4MgjoVUrvxNJHFPLGjAHpIa45twZLD6t9v/w903dyoiGCwHNBCkSVgJc55xbYGb7APPNbJZzrmZzm/tAPW17d8QRR5CZmcl7773nW9EWCoXo27cvHTt2ZPz48TRt2rTO9p0lxIzaAAAgAElEQVSbm8ugQYNITk7m7bff9m0oYocOHXjwwQe57bbbeOKJJ8jMzKRXr16+ZIkDMd82JVxPG3gV6pQp0KMHnH8+vP02JGm6CIkMFW0Bk5mUzphGq6HR6rraYx3tRyT2OefWAGvCv281s2+A1kBMfTBKqG+yayA1NZW+ffv6el3bkiVL+OSTT/jkk0+YNWsWjz76KKeddlqt97thwwYGDRrExo0bef/99+nSpUsdpK2drKwsbrjhBr9jxLR4aZsgAdunAw6AceNgzBh44gnvViQC9HWAiCQkM+sAHA7M2WX7GDObZ2bz1q1b50e0PSotheTorxISc/r37893333H6tV19QVY9eTk5AAwZcoUWrVqxemnn84555xTq/XjCgoKGDp0KMuWLePVV1+lR48edRVXAqSytin8WGDbp9LwhGoJ2T5dfDH07Qu33AKbN/udRuKUijYRSThmlglMA65xzm0p/5hz7nHnXLZzLrt58+b+BNwD57wZp2XP/F6vLScnh0aNGjFixAjmzp3L7bffzssvv0y3bt145ZVXqr2/4uJizjrrLObMmcOUKVO0Blqc2lPbBMFun8rWX0/I9skMHnwQ1q+HO+/0O43EKRVtIpJQzCwV70PRc8656X7nqS4VbVVz+OGH06hRI9+GSM6ZM4ejjjqKpKQkUlNTue2225g3b16Net1CoRAXXnghb7zxBo888ginn356hNOLH+KhbYIEbp+OOMK7rm3cOFi+3O80EodUtIlIwjBv1eEngW+ccw/4nacmVLRVTXJyMv369fOlaCsoKGDhwoW7Tcpx6KGH/qLX7eCDD2bGjBl73Jdzjuuuu45nn32Wv/zlL4zR9TJxKV7aJkjw9unOOyElBW66ye8kEodUtIlIIukNnAcMMLMvwj8n+x2qOlS0VV3//v1ZtmwZubm5UT3uvHnzCIVCFc6kWL7XrWXLlpx22mmce+65lfa63XPPPYwbN46rrrqKsWPHRjq6+Ccu2iZI8PapVSu4+WaYOhU+/NDvNBJnVLSJSMJwzn3knDPnXHfn3GHhn9f9zlUdKtqqrl+/fgB8/PHHUT3unDne/BFHHXVUpc8p3+v20ksvVdjr9sQTT/D73/+es88+mwcffBDTH3zcipe2CdQ+cd110LYtXHsthEJ+p5E4oqJNRCSGqGirvnr16kX1eDk5OXTu3JlmzZrt8Xl76nWbMWMGv/3tbxk0aBDPPPMMSVr7SQJORVtYgwZw992wYAH8859+p5E4ov8FRERiSCiktVuras2aNQBRXXzaOUdOTk61FpnetdetW7dujBw5kuzsbKZOnUpawi18JbFIRVs5Z58NvXrB2LGwbZvfaSRO6L9+EZEYop62qitbo61Vq1ZRO2Zubi5r1qyhZ8+e1Xpd+V63Nm3a0KVLF1577TUyMzMjlFSkbpUVbcLPSwCsWQP33ON3GokTKtpERGKIiraqK+tpa9GiRdSOWbaodnV62so79NBDmTdvHl9++eVeh1eKBInapl306uX1uN13H6xY4XcaiQMq2kREYog+GFXd6tWrad68eVSHF+bk5JCenk737t1rvA8z0zVsEnPUNlXg7ru925tv9jeHxAX9ryAiEkP0wajq1qxZE9Xr2cAr2o444ghdhyYJR21TBdq1g+uvhylTIDyrrEhNqWgTEYkh+mBUdatXr47q9WxFRUUsWLCg2tezicQDtU2VuOkmaNgQJk70O4nEOBVtIiIxRLNHVt2aNWuiWrQtXLiQnTt31vh6NpFYprapEpmZcMop8MorUFzsdxqJYfrnJSISQ0pLITnZ7xTBV1paSl5eXlSHR9Z2EhKRWKa2aQ/OOAM2bIAPPvA7icQwFW0iIjFEH4yqZt26dYRCoaj2tM2ZM4eWLVvSpk2bqB1TJCjUNu3BSSdBRgZMm+Z3EolhKtpERGJIaamGIFVF2Rpt0e5p69WrF6YLeyQBqWjbg/r1YcgQmD7dO1EiNbDX//rN7Ckzyzezr8pta2Jms8xsafg2K7zdzOwhM1tmZgvNrEckw4uIJBp9MKqasjXaotXTtn79epYtW6ahkZKw1DbtxRlnQH4+fPSR30kkRlXl+9pngJN22XYzMNs51wWYHb4PMBjoEv4ZAzxSNzFFRMQ570cfjPYu2j1tc+fOBdDMkZKwQiG1TXt08smQng5Tp/qdRGLUXos259yHwIZdNg8DJoV/nwQML7f9n86TAzQ2s+gukiMiEqdCIe9WH4z2btOmTQBkZWVF5Xg5OTkkJSWRnZ0dleOJBI162vYiMxMGD/aGSJY15iLVUNMrI1o459aEf88DWoR/bw2sLPe83PC23ZjZGDObZ2bz1v2k8b0iIntTdimEPhjtXcOGDQHYsmVLVI6Xk5ND9+7dycjIiMrxRIJGRVsVnHkmrF4N4ZlmRaqj1pezO+cc4Grwusedc9nOuezmTfWvXERkb1S0VV1ZD9vGjRsjfqxQKMTcuXM1NFISmoq2Khg6FNLSNERSaqSmRdvasmGP4dv88PZVQNtyz2sT3iYiIrWkoq3qolm0fffdd2zevFmTkEhCU9FWBQ0bwoAB8NprfieRGFTTom0mMDr8+2jg1XLbzw/PItkL2FxuGKWIiNSCiraqi2bRpkW1RVS0VYlzsGQJtG279+eK7KIqU/5PAT4FDjCzXDO7CLgbGGhmS4ETwvcBXgeWA8uAicBlEUktIpKAVLRVXbSLtkaNGtG1a9eIH0skqLSGZBXMnQvLl8O55/qdRGJQyt6e4Jw7u5KHjq/guQ64vLahRERkdyraqi6aRducOXPo2bMnSfrEKglMPW1V8PzzUK8enH6630kkBul/GBGRGKGireoaNWoERL5o27ZtG4sWLdLQSEl4Ktr2oqQEXnzRm4wk3D6JVIeKNhGRGKGireqSk5Np2LBhxIu2efPmEQqFVLRJwlPRthfvvQdr18I55/idRGKUijYRkRhRVrRpFF7VZGVlRbxomzNnDgBHHXVURI8jEnQq2vbi+ee92SNPPtnvJBKj9F+/iEiMaNwYUlJg6VK/k8SGaBRtOTk5dOnShaZNm0b0OCJB17w5fP89FBf7nSSAduyAadPgjDMgPd3vNBKjVLSJiMSIsiV+pk3zZo6WPcvKymLTpk0R279zjpycHA2NFAGGDYONG+H99/1OEkCvvQZbt2popNTKXmePjIb5CwvXJ7dcVgCs9ztLDTVD2f2g7P6oavb2kQ6SiM44A377W1i4EA491O80wZaVlcW3334bsf2vXLmSvLw8evbsGbFjiMSKQYMgI8P7UmngQL/TBMzzz0OLFtC/v99JJIYFomhzzjU3s3nOuWy/s9SEsvtD2f0Ry9njwfDhcOml3gcjFW17FunhkVpUW+Rn9evDkCHwyiswYYKub/ufTZu8nrZLL9VJkVrR8EgRkRiy777Qr59XtMmeZWZmRnR4ZE5ODunp6XTv3j1ixxCJJWecAfn58NFHficJkBdegKIiDY2UWlPRJiISY844AxYvhm++8TtJcO3cuZOpU6dyxBFHROwYc+bM4YgjjiA1NTVixxCJJSef7M2zoS+VwkpK4N574Ygj4Mgj/U4jMS5IRdvjfgeoBWX3h7L7I5azx4XTTvNu9cGochMnTmTVqlX86U9/isj+i4qKmD9/voZGipSTmeld2zZ9OoRCfqcJgBdfhOXL4ZZbwMzvNBLjAlO0Oedi9oOgsvtD2f0Ry9njRevWcPTRKtoqs2PHDu6880769evHgAEDInKML7/8ksLCQhVtIrs480xYtQrmzvU7ic9CIfjrX+GQQ+DUU/1OI3EgMEWbiIhU3RlnwBdfeF/iyi899thj5OXlcccdd2AR+na7bBISzRwp8ktDh0JqKkyd6ncSn73yijeGfexYSNLHbak9/S0SEYlBp5/u3aq37ZcKCgq46667GDBgAMcee2zEjjNnzhxatWpFmzZtInYMkVjUuDGccEKCryfpnNfL1qULjBjhdxqJE4Eo2szsJDP7zsyWmdnNfufZEzNra2bvmdliM/vazK4Ob29iZrPMbGn4NsvvrBUxs2Qz+9zM/h2+39HM5oTP/YtmluZ3xoqYWWMzm2pm35rZN2Z2dAyd82vDf1e+MrMpZpYe1PNuZk+ZWb6ZfVVuW4Xn2TwPhd/DQjPr4V/yxNOxI/TooaJtV4888gj5+fncfvvtET1O2aLakerJE4llZ5wBP/wAn3/udxKfvPGG9+Z//3tN8y91xveizcySgQnAYKAbcLaZdfM31R6VANc557oBvYDLw3lvBmY757oAs8P3g+hqoPycc/cADzrnOgMbgYt8SbV344E3nXMHAofivYfAn3Mzaw1cBWQ75w4BkoGRBPe8PwOctMu2ys7zYKBL+GcM8EiUMkrYmWfCnDmQm+t3kmDYtm0b99xzDwMHDqRPnz4RO866dev473//q6GRIpUYNsyrVRLySyXn4M9/hnbtYNQov9NIHPG9aAOOApY555Y754qAF4BhPmeqlHNujXNuQfj3rXjFQ2u8zJPCT5sEDPcnYeXMrA0wBHgifN+AAUDZyPOg5m4E9AOeBHDOFTnnNhED5zwsBahvZilAA2ANAT3vzrkPgQ27bK7sPA8D/uk8OUBjM2sZnaQC3rfZkKAfjCowYcIE1q9fH/FetrnhGRY0CYlIxZo1g+OO865rS7ghkq+9Bjk5cNNN3sV9InUkCEVba2Blufu54W2BZ2YdgMOBOUAL59ya8EN5QAufYu3JOOBGoGwi3qbAJudcSfh+UM99R2Ad8HR4aOcTZpZBDJxz59wq4D5gBV6xthmYT2yc9zKVneeY/bcbL7p2hexseOghb+3WRLZlyxb+9re/MXjwYI4++uiIHisnJ4fk5OSIrgEnEuvOPReWLPFqmITx8ccwciQcfDBceKHfaSTOBKFoi0lmlglMA65xzm0p/5hzzgGB+m7JzIYC+c65+X5nqYEUoAfwiHPucKCAXYZCBvGcA4Sv/xqGV3i2AjLYffhhzAjqeU5kd9zhzSD5xBN+J/HX3//+dzZs2BDxXjbwirbu3buTkZER8WOJxKpRo6BzZ2/yxIRYs23ePG918dat4Z13vFXGRepQEIq2VUDbcvfbhLcFlpml4hVszznnpoc3ry0bGha+zfcrXyV6A6ea2Q94Q1AH4F0n1jg8bA+Ce+5zgVzn3Jzw/al4RVzQzznACcD3zrl1zrliYDren0UsnPcylZ3nmPu3G49OOgn69vUuoSgo8DuNPzZv3sx9993HKaecwpFHHhnRY4VCIebOnavr2UT2IjXVa5cWLYIpU/xOE2FffgknnghNm8Ls2bDffn4nkjgUhKLtM6BLeDa9NLxJGmb6nKlS4evAngS+cc49UO6hmcDo8O+jgVejnW1PnHO/d861cc51wDvH7zrnzgXeA84MPy1wuQGcc3nASjM7ILzpeGAxAT/nYSuAXmbWIPx3pyx74M97OZWd55nA+eFZJHsBm8sNo5QoMYO77oK8PPj73/1O44/x48ezadOmqPSyLVmyhC1btuh6NpEqGDECDjsMbrstjodwL17srXGQkQHvvgtaBkQixFwArhA1s5PxrrdKBp5yzv3V50iVMrM+wH+ARfx8bdhYvOvaXgLaAT8CI5xzu07oEAhmdhxwvXNuqJntj9fz1gT4HBjlnCv0M19FzOwwvAlU0oDlwAV4XzoE/pyb2e3Ar/BmHv0cuBjv2q/AnXczmwIcBzQD1gJ/BGZQwXkOF6EP4w333A5c4Jyb50fuSMnOznbz5sXGWzrlFPjoI2+oZFYgF7+IjPXr19O5c2f69+/PK6+8EpVj5ubmss8++9CoUaOoHE/qnpnNd85l+52jNmKlfXrjDW/U4IQJcNllfqepY0uXQr9+3u8ffuityyZSC3tqmwJRtImIBFGsfCgCWLjQ+0b7ppu8nrdEsGnTJk444QQWLVrEvHnz+L//+z+/I0mMUNEWPc7Bscd69c2yZV6HVFxYtgwGDIAdO+CDD6BbkFerklixp7YpCMMjRUSklrp3h7PPhvHjYU0CDFLdvHkzgwYNYuHChUyfPl0Fm0hAxd0Q7lDIeyOHHgrbtsGsWSrYJCpUtImIxIk77oDiYvjLX/xOEllbtmzhpJNOYsGCBUydOpUhQ4b4HUlE9qB3bxgyBO65BzZu9DtNLSxZ4nUbXnWVNwPUF194QxxEokBFm4hInOjUCX7zG3j8cfjvf/1OExnbtm3j5JNP5rPPPuOll17i1FNP9TuSiFTBnXfC5s3wt7/5naQGSkrg3nu93rWvvoJnnvEu1mvXzu9kkkBUtImIxJFbb/Wm2v7jH/1OUvcKCgoYMmQIOTk5TJkyhdNOO83vSCJSRTE7hPurr+CYY+DGG701VhYvhtGjvXGfIlGkok1EJI60bOmN3Hn+eW99pHixfft2TjnlFD766COeffZZzjrrLL8jiUg1xdQQ7lDI6xbs0QO+/x5efBGmT/caWREfqGgTEYkzN90EDRvCH/7gd5K6sWPHDoYNG8b777/PpEmTGDlypN+RRKQGOnWCiy/2hnAvX+53mj3Iz/fWKbjpJhg2zOtdGzFCvWviKxVtIiJxJivL+6zxr3/Bxx/7naZ2du7cyemnn87s2bN5+umnGTVqlN+RRKQWyoZw33ab30kqMXu2d+3aBx/AY4/BSy9B8+Z+pxJR0SYiEo+uugpatICbb4bt2/1OUzOFhYWceeaZvPnmm0ycOJHRo0f7HUlEaqlVq5+HcOfk+J2mnJISuOUWGDjQ++Zr7lwYM0a9axIYKtpEROJQRgb8+c/w0UfQvr13Lcn69X6nqrqioiJGjBjBa6+9xmOPPcZFF13kdyQRqSM33QTNmnnze5x2Gnzyic+BVq6E446Dv/4VLrgAPvsMtPajBIyKNhGROPWb33gjfHr18maTbNcOrrgi4NeSACUlJYwcOZKZM2cyYcIExowZ43ckEalDWVneREl/+IPXRvXuDX36wKuvevN/RNXMmd5wyC+/hOeegyef9L71EgkYFW0iInGsXz/v2ravv4aRI70JALp0gV/9CubN8ztdxZKSkmjZsiXjx4/nsssu8zuOiERAixbeaIAVK7xlAHJzYfhw6NYNnngCdu6MQgjnvIN37AgLFsA550ThoCI1o6JNRBKKmZ1kZt+Z2TIzu9nvPNHSrRs89RT88APccAO8+SYceSQMGOCtEeuc3wl/lpSUxMMPP8xVV13ldxSRqEnUtikz07vGbdkymDIFGjTwRgl06AB33QUbN0bw4GbeRCOffOJ9myUSYCraRCRhmFkyMAEYDHQDzjazbv6miq5WreDuu71LOO67D5Ys8Wa27t4d/vlPKCryO6HHdPG/JBC1TZCS4o0GmD8f3nkHDjsMxo6Ftm3h2mu9HrmIaNoU6tWL0M5F6o65IH29KiISQWZ2NPAn59yg8P3fAzjn7qro+dnZ2W5eUMcQ1pGiInjhBbj3XvjqK2jdGgYN8q4rCYWgtPSXP7tuK7vfrh08/bTf70akasxsvnMu2+8cZarbNkFitE9fful9uTRlinf/lFOgSZOqt0tlP+PHe19MiQTdntqmlGiHERHxUWtgZbn7uUDP8k8wszHAGIB27dpFL5lP0tLg/PPhvPO8IZMPPODdJif//JOUtPf7paV+vxORmLbXtgkSr3069FCYPNmb1HHcOJg2zSvIqtM2JSf7MLmJSASoaBMRKcc59zjwOHjfZPscJ2rMYPBg70dEgilR26d27bwvlB54wO8kIv7RNW0ikkhWAW3L3W8T3iYi4ie1TSKyRyraRCSRfAZ0MbOOZpYGjARm+pxJRERtk4jskYZHikjCcM6VmNkVwFtAMvCUc+5rn2OJSIJT2yQie6OiTUQSinPudeB1v3OIiJSntklE9kTDI0VERERERAJMRZuIiIiIiEiAqWgTEREREREJMBVtIiIiIiIiAaaiTUREREREJMBUtImIiIiIiASYijYREREREZEAU9EmIiIiIiISYCraREREREREAkxFm4iIiIiISICpaBMREREREQkwFW0iIiIiIiIBpqJNREREREQkwFS0iYiIiIiIBJiKNhERERERkQBT0SYiIiIiIhJgKtpEREREREQCTEWbiIiIiIhIgKloExERERERCTAVbSIiIiIiIgGmok1ERERERCTAVLSJiIiIiIgEmIo2ERERERGRAFPRJiIiIiIiEmAq2kRERERERALMnHN+ZxARCSQzWwf8WMe7bQasr+N91jVlrBvKWDcikbG9c655He8zqiLQPiXq34W6FgsZITZyJmLGStsmFW0iIlFkZvOcc9l+59gTZawbylg3YiFjPIiF86yMdScWcirjL2l4pIiIiIiISICpaBMREREREQkwFW0iItH1uN8BqkAZ64Yy1o1YyBgPYuE8K2PdiYWcyliOrmkTEREREREJMPW0iYiIiIiIBJiKNhERERERkQBT0SYiEiVmdpKZfWdmy8zsZr/z7MrM2prZe2a22My+NrOr/c5UETNLNrPPzezffmepjJk1NrOpZvatmX1jZkf7nWlXZnZt+M/5KzObYmbpAcj0lJnlm9lX5bY1MbNZZrY0fJvlZ8Z4pLap7gS9fVLbVONMvrdNKtpERKLAzJKBCcBgoBtwtpl18zfVbkqA65xz3YBewOUBzAhwNfCN3yH2YjzwpnPuQOBQApbXzFoDVwHZzrlDgGRgpL+pAHgGOGmXbTcDs51zXYDZ4ftSR9Q21bmgt09qm2rmGXxum1S0iYhEx1HAMufccudcEfACMMznTL/gnFvjnFsQ/n0r3n/mrf1N9Utm1gYYAjzhd5bKmFkjoB/wJIBzrsg5t8nfVBVKAeqbWQrQAFjtcx6ccx8CG3bZPAyYFP59EjA8qqHin9qmOhL09kltU80FoW1S0SYiEh2tgZXl7ucSwA8dZcysA3A4MMffJLsZB9wIhPwOsgcdgXXA0+FhUk+YWYbfocpzzq0C7gNWAGuAzc65t/1NVakWzrk14d/zgBZ+holDapvqTtDbJ7VNdSuqbZOKNhER+QUzywSmAdc457b4naeMmQ0F8p1z8/3OshcpQA/gEefc4UABARvSF772Yhjeh7hWQIaZjfI31d45b50irVWUoILaNkHMtE9qmyIkGm2TijYRkehYBbQtd79NeFugmFkq3oei55xz0/3Os4vewKlm9gPeEK4BZvasv5EqlAvkOufKegKm4n1QCpITgO+dc+ucc8XAdOAYnzNVZq2ZtQQI3+b7nCfeqG2qG7HQPqltqltRbZtUtImIRMdnQBcz62hmaXgXVs/0OdMvmJnhXevwjXPuAb/z7Mo593vnXBvnXAe88/eucy5w38A65/KAlWZ2QHjT8cBiHyNVZAXQy8wahP/cjydgExKUMxMYHf59NPCqj1nikdqmOhAL7ZPapjoX1bYpJZI7FxERj3OuxMyuAN7Cmw3rKefc1z7H2lVv4DxgkZl9Ed421jn3uo+ZYtWVwHPhD8HLgQt8zvMLzrk5ZjYVWIA3M9/nwOP+pgIzmwIcBzQzs1zgj8DdwEtmdhHwIzDCv4TxR21TwlHbVANBaJvMG4IpIiIiIiIiQaThkSIiIiIiIgGmok1ERERERCTAVLSJiIiIiIgEmIo2ERERERGRAFPRJiIiIiIiEmAq2kRERERERAJMRZuIiIiIiEiAqWgTEREREREJMBVtIiIiIiIiAaaiTUREREREJMBUtImIiIiIiASYijYREREREZEAU9EmIiIiIiISYCraREREREREAkxFm4iIiIiISICpaBMREREREQkwFW0iIiIiIiIBpqJNREREREQkwFS0iYiIiIiIBJiKNhERERERkQBT0SYiIiIiIhJgKtpEREREREQCTEWbiIiIiIhIgKloExERERERCTAVbSIiIiIiIgGmok1ERERERCTAVLSJiIiIiIgEmIo2ERERERGRAFPRJiIiIiIiEmAq2kRERERERAJMRZuIiIiIiEiAqWgTEREREREJMBVtIiIiIiIiAaaiTUREREREJMBUtImIiIiIiASYijYREREREZEAU9EmIiIiIiISYCraREREREREAkxFm4iIiIiISICpaBMREREREQkwFW0iIiIiIiIBpqJNREREREQkwFS0Sa2Z2TNm9pfw733N7Lsa7udRM7u1btOJSKJS2yQiQaX2SapLRVuCMLMfzGyHmW0zs7XhxiKzro/jnPuPc+6AKuT5tZl9tMtrL3HO/bmuM5nZaDObb2ZbzCzXzP5mZil1fRwRqb4Eb5tGmtl3ZrbZzPLNbJKZNazr44hIzSRy+7TLcWebmdNnJ3+paEsspzjnMoEeQDZwy65PiNN/kA2Aa4BmQE/geOB6XxOJSHmJ2jZ9DPR2zjUC9gdSgL/4G0lEdpGo7RMAZnYukOp3DlHRlpCcc6uAN4BDAMLfnlxuZkuBpeFtQ83sCzPbZGafmFn3steb2eFmtsDMtprZi0B6uceOM7Pccvfbmtl0M1tnZj+Z2cNmdhDwKHB0+NurTeHn/m+oQPj+b8xsmZltMLOZZtaq3GPOzC4xs6XhjBPMzCp5v4+Ev8UqCr/354DedXEuRaTuJGDbtNI5t77cplKgc23OoYhERqK1T+HnNwL+CNxY2/MntaeiLQGZWVvgZODzcpuH4/VCdTOzw4GngN8CTYHHgJlmVs/M0oAZwGSgCfAycEYlx0kG/g38CHQAWgMvOOe+AS4BPnXOZTrnGlfw2gHAXcAIoGV4Hy/s8rShwJFA9/DzBlXxFPQDvq7ic0UkShKxbTKzPma2GdgazjuusueKiH8SsX0C7gQeAfL28ByJEhVtiWVG+JuZj4AP8P4xlrnLObfBObcDGAM85pyb45wrdc5NAgqBXuGfVGCcc67YOTcV+KyS4x0FtAJucM4VOOd2Ouc+quS5uzoXeMo5t8A5Vwj8Hu/bpQ7lnnO3c26Tc24F8B5w2N52amYX4g1vuFakLTwAACAASURBVK+KOUQk8hK2bXLOfRQeHtkGuBf4oYo5RCQ6ErJ9MrNsvFFJf6/isSXC4nYMrlRouHPunUoeW1nu9/bAaDO7sty2NLxGxAGrnHOu3GM/VrLPtsCPzrmSGmRtBSwou+Oc22ZmP+F94/RDeHP5b362A3u8ONjMhuN9A3XCLkOSRMRfCd02hfezyszexPtWvEcNcolIZCRc+2RmScA/gKudcyV7GEEpUaSeNilTviFZCfzVOde43E8D59wUYA3Qepcx0O0q2edKoJ1VfIGuq2BbeavxGkAAzCwDb7jBqr29kYqY2UnARLwLihfVZB8i4ou4bpt2kQJ0qoP9iEh0xGv71BBvVNKLZpbHz72CuWbWt5r7kjqiok0qMhG4xMx6mifDzIaY2T7Ap0AJcJWZpZrZ6Xhd+RWZi9dQ3R3eR7qZlU0AshZoEx7nXZEpwAVmdpiZ1cMbjjDHOfdDdd9MeIz3c8AZzrm51X29iARGvLVN55pZu/Dv7YG/ArOrux8RCYR4ap824/XaHRb+OTm8/QhgTjX3JXVERZvsxjk3D/gN8DCwEVgG/Dr8WBFwevj+BuBXwPRK9lMKnII3G9oKIDf8fIB38SYDyTOz3YYqhoci3ApMw2u8OgEja/iWbgUaAa+HZ1zaZmZv1HBfIuKTOGybugGfmFkB3vT/34Xfn4jEmHhqn5wnr+wHWBd+aG34vYgP7JfDa0VERERERCRI1NMmIiIiIiISYCraREREREREAkxFm4iIiIiISICpaBMREREREQmwQCyu3axZM9ehQwe/Y4hIHZo/f/5651xzv3PUhtomkfik9klEgmhPbVMgirYOHTowb948v2OISB0ysx/9zlBbaptE4pPaJxEJoj21TRoeKSIiIiIiEmAq2kRERERERAJMRZuIiIiIiEiAqWgTEREREREJMBVtIiIiIiIiAaaiTUREREREJMBUtImIiIiIiASYijYREREREZEAU9EmIiIiIiISYCraREREREREAkxFm4iIiIiISICpaBMREREREQkwFW0iIiIiIiIBpqJNREREREQkwFS0iYiIiIiIBJiKNhERERERkQBT0SYiIiIiIhJgKtpEREREREQCTEWbiIiIiIhIgKloExERERERCTAVbSIiIiIiIgGmok1ERERERCTAVLSJiIiIiIgEmIo2ERERERGRAFPRJiIiIiIiEmAq2kRERERERAKsVkWbmT1lZvlm9lW5bU3MbJaZLQ3fZtU+pohI1altEpEgUtskIjVV2562Z4CTdtl2MzDbOdcFmB2+LyISTc+gtklEgucZ1DaJSA3Uqmhzzn0IbNhl8zBgUvj3ScDw2hzj/9m777gqy/4P4J/7HOZB2QiIgAPco9w2HGmlWZk2bNCwzHpMradtw+ZTPe209Ut7WtpO09K0LMvc4t5K4EAB2euwzjnX748rRBIUhHOu+z7n8369eGEK5/6QeHF9r0nu5cMP5RuRM7FtosY6eBC46y6guFh1EnJnbJvobDz9NPDLL6pTkGpeTnjNSCFExt+/zgQQWdcHaZo2CcAkAIiLi3NCDNKb/Hxg2jSgqgoYPBhITFSdiDwM2yaq13/+A8yZA4SEAC+9pDoNeZgGtU0A2ydPtGkT8MwzQHQ0sH8/0KKF6kSkilMPIhFCCACinj/7QAjRVwjRNyIiwpkxSCf+9z/AagXMZuDBB1WnIU/GtolOlpsLzJ0L+PkBb7wB/PWX6kTkqU7XNv3952yfPMysWYCvL5CRwQElT+eMoi1L07RoAPj7/XEnPIMMxm4H3n5bzrA99RSwaBGwfLnqVORh2DZRnWbPBsrLZbvk7Q089JDqRORh2DZRnbKygC++ACZOBG68EXj1VbmUmzyTM4q2RQBu/fvXtwJY6IRnkMH88INsaKZNA+67D2jXTr632VQnIw/CtolOYbMB77wDDB8OXHwxMH06sGABsGKF6mTkQdg2UZ0++ACorASmTpWzbCYT8PDDqlORKk098v8LAGsBdNI0LV3TtDsAvATgYk3TDgAY8fd/k4ebOROIiwPGjJFLkF59Fdi1SzZIRM2NbRM11PffA+npckAJAO6/H4iPl4NKdrvabOR+2DZRQ1VWAu+9B4wcCXTqBMTGAo88AnzzDbBypep0pEKTDiIRQtxQzx8Nb8rrknvZvl2OWv/3v4DX399xY8cCw4YBM2YA118PhIaqzUjuhW0TNdRbb8mZ/9Gj5X/7+wOvvAJcd508mOSuu9TmI/fCtoka6ttv5T62k0/cfugh+d/33Qds3CjPCCDP4dSDSIgAuYnW31+uya6macCbb8oTJZ95Rl02IvJcmzcDq1bJpUcnd36uuQa48ELgiSeAggJ1+YjIc82cCXTsCFx6ac3vWSzAyy8DW7YAH32kLhup4Ywj/92a1SqX0lS/ZWcDwcFAeHjNW0SE/D1TA0viqipZvOTlybeTf11YCIwbB3Tv7tyvy1lycuSpbLfccupsWs+ewJ13yv0kd98NdOmiJiORO7DbgczM2u2T2Szbo5Pbp/BweRJZQwgBFBWd2i5V/3dUFDBhgnO/LmeaORMICDj1a9A0OQPXpw/w3HPAa6+pyUfkDqrbkZPbpsJC2Seo7jNVt02BgfLfX0OUl9fdLuXlAaWlsn8RFeXcr81Z1q+Xb7NmndqXHD9eHuz2+ONyRUBgoJqM5Hos2k5SWSmPej65Yal+O3JEvs/Pb9hrmUxAWFjtxigoqKYDdHLjUlJy+tdaswZYurTpX58Kc+bIhnXq1Lr//LnngC+/lPtIfvrJtdmIjOToUeDw4VPbpOq3Y8cavgerZcvag0xhYfJz/1mcFRSc+TWHDAHat2/61+dqx4/XnMoWHHzqn597LnD77bKwu+suOeJNRKcqLQVSU09tk05up87Uz6nm7X3qILjFItuif/adyspO/1pFRXKpsxHNnCmLsVtvPfXPqlcq9esHPP+8nHkjz6DJK0HU6tu3r0hOTlaa4eBBeXpYamrt34+IANq0kRtA27Sp/RYbKxuVwkI5o1T9lp1d+7+rf6+wUBZuoaHyAtfQ0Nq/ruv3XnhBjrQcP153x0LPbDa5V6RTp9Mf7//668ADDwCLFwOXXea6fORcmqZtEkL0VZ2jKfTQNgkh9y/MnFn79/39T22XTv7vmBj5ufW1R//8b2/vutug+tqowkKga1d5qNADD6j5f9MUzz8PPPkksGcP0Llz3R+TlQUkJsrC9IcfXJuPnIvtU/NYs0b+3C4srPk9TZMXQdfXd2rTRvaF8vMb1j6Vlp6+n1TXr6+/HkhJAQ4caPjMnV4cOyYPQ5oyRd4bWZ8JE4B584Ddu4GEBNflI+c6XdvEog2yYBs6VDY6r70mv/nbtAFat5YnHaq0di1w3nlyieFNN6nN0ljffCOn7hcuBK68sv6Pq6wEevSQDeuOHbLz6ArFxfKHgxFnCYyAnaKmE0L+4H73XWDSJHn6anWnJyREfWfk3HPlKPjq1WpzNFZlJdC2rVyifaZVDC+/LE9sW7YMuOQSl8QDAOzcKZeM86AB52D71HSrV8uTDaOi5CBIXJxsm6KiXPdzvD4ffCBnyLdtk//OjWTGDPn/c//+0xdjGRlyBcDw4fIUXFc5flyuwIiOdt0zPcnp2iaPP4gkLU2OohYWytmg22+XF0C3b6++YAOAAQPkP4z581UnabyZM2ufylYfHx9ZLO/bJ/e3ucK+fXK/SufOxl16Su7N4QDuuUcWbA89BLz/vhzR7tlTjiarLtgAud927VrZeTCS776Tme+998wfe++9QIcOwL//7Zp7JW02Waj36CEH6njtAOnRqlWyYIuOBn7/Xe6zGjRIzqypLtgAOcClacbrO1VUyLZ+9Ogzz55FRwOPPSYHxn/91TX5VqyQ/aaePeUMH7mWRxdtqalyhq24WH7D9+mjOtGpTCZ5PP7SpfIQFKOo71S2+oweLUexn3lGLodwpuXLgYED5dKMTp3k/9/ff3fuM4kao7pge+89eZHqf/+rjyLtn8aOlbOBCw12FfDMmXLZ48mnstXH11cuAd29W3amnKmgQBbm77wDXHQR8NVX8jAFh8O5zyVqjOqCrXVr+bMzJkZ1olNFRgIXXAAsWKA6SeN89ZVcAdSQASVADia1ayeX0Dt7UGn2bNlPi4qS1zeNGCGXoJLreGzRdnLBtnw50Lu36kT1GzdOFmw//6w6ScPVdypbfTRNrt0uLpZLA5yl+qLKNm3kHScrVshZ1csvB9atc95ziRrK4QAmT5YFwqOPAi+9pM+CDQC6dZPFj5FGszdskP/Wp05t+Am/Y8bIIuqpp+QBCM6QkiIHk37/Xd7D9Ouv8nkffSQv/tbBTgYi/Pmn/BkaEyN/frZurTpR/caNk/fEGqWwEEKeWtuli1zy2BB+fvKwlZ07ZVHlDHa7LA4nTZKF2tq1st9cWSlzHj7snOdSHYQQyt/69OkjXOnIESFiY4UIDRVi82aXPvqsVFYKERIixM03q07SMFlZQvj4CDF5cuM/d8oUIUwmIbZvb95MVVXytQEhRo8WorCw5s+OHRMiIUGIoCBjfD8YBYBkoYP2pSlvrm6bhBDinnvk9+n06UI4HC5/fKM98ogQXl5C5OWpTtIwN90kRMuWQhQVNe7ztm+XbdPUqc2f6bffZBsfFibE77/X/L7DIcSDD8rvh4cfNsb3g1GwfWq8deuECAgQolMn+XNT79LS5L+dl19WnaRhVq2Sed97r3Gf53AIMWSIbD+aux0uLBRi1CiZ6777ZF+q2qZNst+UkGCM7wejOF3bpLzRES5ueCoqhBg4UIgWLYzVQb/1ViGCg2UBp3fPPSe/s/bsafzn5uTIzsvw4c3XQcnPF+KSS2SmBx4QwmY79WMOHRIiLk6I8HAhdu1qnud6OnaKGm/27JrvU6N00Netk5k//VR1kjM7dkwIb28h7r337D7/X/8Swmxu3jbigw9k0dulixApKaf+ucMhB8AAIZ55pvme6+nYPjVOVpYQMTFCtG9vrA56796yz2cE110n+3klJY3/3C1bhNA0WVg1l7/+EqJrV9k+vf9+3R+zZo0s5Lt2FSI7u/me7clYtJ2kehT7m29c9shmsXChzP3zz6qTnF5FhRDR0UJceunZv8bMmfJr/f77puc5cECIzp1lozNnzpk/Njpavh040PRnezp2ihonOVkIX18hLr647oEFvbLbZWfuqqtUJzmzGTNkx+Zs/31nZ8tO1SWXNL2ottlkBwuQ7WVBQf0fa7cLcdtt8mNffbVpzyWJ7VPDVVUJMWyYEH5+sjgwkuefl/9ujh5VneT0Dh+WA0IPPnj2r3HnnbKvczYD5v+0cqUcxA4JEeLXX0//sb/9Jr83zj1XDpJT07Bo+9vcufIrvv9+lzyuWVmtcjTj7rtVJzm9zz+X/48XLz7716islKPOHToIUV5+9q/z++9yCWxoqBArVjTsc3btkg1VXJwQBw+e/bOJnaLGyMkRIj5eLts24mjllClC+Puf3Qixq5SXC9GqlRCXX96013njDdnG/fDD2b9GYaEQl10mX2fatNpLjupjs8mReECId989+2eTxPap4R55RH7fffyxSx7XrHbvltnfeUd1ktObPl0uv05LO/vXyMoSIjBQti1N8dFHckVCx45C7NvXsM9ZskR+zqBBQhQXN+35no5Fm5D7Efz9hRg82BhLDOvywguyKNKzAQOESEyUI8NNsXSpaNJa9Dlz5IhT586NH1XfvJnrtJsDO0UNY7MJMXKk3Ae6fr3TH+cUa9cK8eijQuTmqk5Sv08+Ec2yWqGyUu7pSUyUKwsaKzVViG7d5Kh6Y/euVFYKccUVxu1A6wnbp4aZP19+v911l9Mf5TTTpjV84FYFq1XuRxs7tumv9cor8u/rp58a/7k2m9w7C8gtKo3dH/fdd7JdGzZMfk10djy+aCsokB3w6GghMjKc+iiPVr23ZebM5nm90aPlgQGZmQ3/HJtNzqQCcgnT2U7Vc51207FT1DBPPSXOavM5NZzDIUSfPnIGvzn2Ci5eLP/OXnutcZ/3559yJj84WIjly8/u2WVlQowYIUflv/767F6D2D41xL598mdwv35NW/VCpzdnjmxPmqOwrKiQ/d3OnRs3QVFcLMSVV8oc//rX2U9ufPaZXII+atTZDWrR6dsm5Y2OcHLD43DIvRZeXvIHJjlP9alsJ5/M2BR798q/t4kTG/bxJy85mjq1YUuOTmfFCq7Tbgp2is5syRL5A+6WW4xz8IgRrV4tmr0wHjlSzsgfP96wj69ecpSY2PAlR/UpKRHiggtk+9iUZZqejO3T6ZWUCNG9u5wBOnTIaY/xeA6HED17yrfm+hlQfQbCW2817OMPHZLPN5mEmDWr6Tn+7//k86++uun9ME/k0UXbSy/Jr/KNN5z2CBJNP5WtPv/+t+zUnumkz7Q0+QPGbG7e/R4//cR12meLnaLTS02Vm7x79hSitNRpjyHRtFPZ6rN7t2xvzrRszG5v2pKj+hQWCtG3rzy85pdfmuc1PQnbp/o5HELceKP82btsmVMeQX9bsUK2DWc6KK0xHA45Gx8SIvdLn87atXKvb2Cg3JbSXKr3/iYlNX27jKfx2KLt11/lyMH48RzFdramnspWn/x8uZxo8OD6/w5XrRIiIkJ2ypzReZk/n+u0zwY7RfUrK5NHUQcF1X3MOzWfI0eafipbfaZNkz9jtm2r+8+Li4UYM0b+pL377ubfT52bK0SPHkJYLFxJ0lhsn+o3a5b8nn3uOae8PJ1k7Fg5m9ncfYsdO2TbdM899X/MvHly0Kd9ezkI1dyqT+6cNIl98MbwyKItM1N25Lt04QyJszXXqWz1ef99+Z1a1/6NTz6RBzgkJsrllM4yb17NOm2u7W8Ydorqd/fd8nt60SKnvDyd5LHHmn4qW31yc+XptMOGndopOXRIiF695LNnznRepyUzUx6M0rKlEBs3OucZ7ojtU902bpSrSy6/nDMkzpaWJtuH6dOd8/r33CNff8eO2r9vtwvxxBPyZ9DgwWeejWuK6dPFiYu5Wbg1jEcWbR9/LL+6DRua/aXpH5rrVLb62GxyCVl8fM1olN0uT6sDZIfJFafWVV98PG4c12k3BDtFdXM45MzIbbc1+0vTPzTnqWz1eftt2S7Mn1/ze2vXChEZKZccnc0pbo115IgQ7drJAnL7duc/zx2wfarbAw/IvdzNtYyX6vfgg3IVwOHDznn9nBy5RHLEiJqCqaRE7jUDhLj9ducfFuJwyBUJgBCPP+7cZ7mL07VNJriplBTAbAbOOUd1EvcmBDBzJtClCzBihHOeYTYDb74JHDoEvP46UFICXH018NJLwKRJwLJlQGioc559sokTgbfeAubPB4YPB378EXA4nP9cci+ZmYDVCvTrpzqJ+/viCyA3F5g2zXnPuOsuoFs34MEHgYoK4PPPgaFDgYAAYO1aYORI5z27Wps2wK+/Av7+wLBhsm3MyXH+c8n9pKQACQlASIjqJO6ttBSYMwcYNw6IjXXOM8LCgKefBpYvB374ATh6FBg8WPZhXntNPt/HxznPrqZpsv82cSLwn/8A48cD69bJviM1nlsXbW3bAt7eqpO4t7VrgU2bZKdI05z3nGHDgLFjgRdfBM4/H1i0SBZQ77/v2r/jadOA//s/+f11xRVAx47AG28ABQWuy0DGlpIi3yckqM3h7qoHlHr2BIYMcd5zvLxkG5CaClx0EXDTTcCAAcD69UDXrs577j+1awf89hvQqxcwfbos5G6/HdiyxXUZyPiqizZyrrlzZb/h3nud+5x//UsOqt97rxwo3L9f9p/uv9+5fbaTaZrsqz32GLB0KTBoENC/P/Dpp3KgixrOrYs2NjzO5+Uli5ebb3b+s159FaiqAtLS5CyXswvF+kyaBBw8CHz5JRAVJRu/mBjZOO7e7fo8ZCws2lyjokIO9jzyiPPbiYsvlu3gmjWyUPrlFyA83LnPrEvHjnLGbedOYMIE4KuvgN69gQsukL+uqnJ9JjIOhwP46y+2Ta4QFQUkJQHnnefc53h7yxVKBw/KWbU1a4DLL3fuM+tiNsuZtvR04J135IqpW2+Vs4xPPCFnAenM3LJoEwI4cIANjyv07y9HbQICnP+s9u2BP/4Atm4FRo1y/vNOx9tbTvOvWiVnGsePBz76SC6TGj4c+P57wG5Xm5H0KSVFDnbExalO4t78/OQM2I03uuZ5H38MLFnimiVHZ9KtG/Dee7KD9NprQEYGcP31cvXJc88BWVlq85E+HTsGlJez7+QKY8YAn33mmoHnkSPlNpKNG4EePZz/vNNp2RKYPFkOcP/8MzBwIPDCC0B8PHDddcCff3Lp5Om4ZdGWlwcUFrLhcUcDB8riTU969wb+9z/ZQXrhBbn8YOxYoEMH4JVX5PcjUbWUFLmUzctLdRJqTqGhcjBJxex/fUJC5EqA/fvlnpbu3YEZM+SAwS23yE4cUTWuAnBfl1wCRESoTlFD0+QKhUWL5PfdfffJFQqDB9f0qcrKVKfUH7cs2tjwkArh4XIvSVoa8O23clT74Yfl3pI77wS2b1edkPSAS7fJ1cxmuSRq2TJgzx65xHvBArlSYuBAYN48oLJSdUpSjX0nUqF9e7n9JT1dnhlgswF33CGXTj76KHD4sOqE+sGijaiZeXnJ0y1//x3Ytk2uW583Tx4QcPPN3Hjrybh0m1Tr3BmYNUvuIZk5E8jPl21UQoJcek6eKyVFLu1t00Z1EvJEAQFyQGn7dmDFCnmA1CuvyJUpzzzDZZOAGxdtmib/oolU6tkT+OADOYL02GPyxKjRo4GiItXJSIXsbKC4mEUbqRcYCEydKmfeliyRHaLBg+UJlOSZUlLkrIfZrDoJeTJNk9emfPedXLl0ww3y6oK77+ZZAW5btMXGAr6+qpMQSaGh8uSkTz6RM3BDh/IwAE9UvQqgQwe1OYiqmUxyL97atXKv26hRwNdfq05FKqSksG0ifYmLkwe2PPaYHAC/5hrP3uvmtkUbR7JJj265RR4IsG+fPOq3uhNPnoFLt0mv2rSRJ7f17y9Pmpw1S3UiciUh2HcifdI0Oeg9cyawcKE8VCU/X3UqNVi0EbnYqFFyCVJhoSzckpNVJyJXSUmRMxtt26pOQnSqkBB5DPeVV8p7MB97jPtIPEVWFlBayr4T6dfUqfJ+3A0bgAsvlNtOPI3bFW0FBUBODhse0rcBA4DVqwGLRS6V/Pln1YnIFVJS5HIPLt0mvfL3l6ffTpoEvPiivCycl3K7P64CICO47jrgp5/kiZLnnSfve/Mkble05ebK93q6j4KoLp06AWvWyD0Eo0fLEybJveXksG0i/fPyAt5/X97p9vHHwFVXyVkYcl85OfI92yfSu4suAlaulINJF1wg+1Gewu2Ktqgo+T4zU20OooZo3Vo2PhdcII/dfv111YnImaKi2DaRMWiaPGb7vffkyPbw4TWDouR+2HciIznnHFmshYfLtumHH1Qncg23K9oCAoCgIHkHDZERBAXJTtE11wAPPAA8+CDgcKhORc4QEwNkZPDvl4zj7rvlcsmtW4HzzwcOHVKdiJwhJka+Z9+p8SqOVWDbxdtgTbGqjuJR2rWT20y6dwfGjgU+/FB1Iudzu6INkI0PGx4yEj8/ucF28mTgtdfkKZOVlapTUXOLiQFsNuD4cdVJiBpu3Di57zYzU+4j2bFDdSJqblFRcnaVfafGKz9cjuItxdjcfzPyluepjuNRIiLkRdwjRgATJ8pTJt358CQWbUQ6YTYDb78NPP+83N92xRVASYnqVNScOJpNRjV4sLwSAJAnt61cqTYPNS9vbyAykm3T2QgaGIQ+G/vAN8YX20duR/rMdAh3rhx0pkULYNEiucXkiSfkKZPuegk3izYiHdE04PHHgTlzgOXLgWHDgKIi1amouVQXbceOqc1BdDZ69JD7SKKj5V1JixerTkTNiX2ns+ffzh/nrjkX4VeEI+XeFOybuA+OCq6DdxUfH+CTT+T2knfeAW64wT23Ibht0ZaZ6b6VNrm/O+4AFiwANm2SRRy5B860kdHFxwOrVgFdugC33cbDSdwJi7am8WrphW7fdUP8k/HI/F8mtl60FRWZFapjeQyTCXjlFeCFF4BvvpGD3+7GbYs2u11eFklkVFdeCUyZIkeNNmxQnYaaQ2Sk/MHCjpH+cDlTw4WFAZ9+Ku9Fffhh1WmoubBoazrNpKHds+3Q9euuKNlags39NqPiGAs3V3r0UXn/7SOPuN9pqG5btAFsfMj4nn9eLkWaNEkeYEHG5uUlN/yzbdKXdenr0G92P2SWuNlPeCfq0UOedvu//wF//KE6DTWHmBggLw8oK1OdxPhaXdsKcdPjUJFeAVshf3i7kqbJeyatVuD++1WnaV4s2oh0LDAQmDUL2LYNeOst1WmoOXA0W3/C/MOwPWs7nvztSdVRDGXGDKBtW3ktQAUnEwyPe26bV+4PuQjoFYCALgGqo3icTp2Axx4DvvgCWLZMdZrmw6KNSOfGjpUnSc6YwTuS3AGLNv1JDEvEtAHT8OGWD7ElY4vqOIZhsQDvvgvs3Qu8/LLqNNRU7Ds1H+sBK4o3FCMyKVJ1FI/16KNAx47Av/4lZ93cgVsWbRER8vh0NjzkDjRNXgWgacA997j3HSSegEWbPj0x+AmEWcLw72X/5v62Rhg1Chg/Xt6PtH+/6jTUFK1by/dsn5oua14WoAGRN7BoU8XXF/i//wPS0uRWE3fglkWb2Sz3AbHhIXcRFwc8+6w8Ynv+fNVpqCliYuQBDu4y8ucugv2C8dyw5/DHoT8wfw//kTXGG28Afn5yRJv1rnFxpq15CCGQNTcLwcOC4RvjqzqORxs6VJ5y+8orwM6dqtM0nVsWbYA8lviPP2SFTeQOpk0DzjlHXhxZWKg6DZ2t+Hj5/pNP1OagU03sPRHdW3XHQ788hHJbueo4hhEdKaltkgAAIABJREFUDbz0EvDbb8DcuarT0NkKCpL7qBcs4M+YpijeUIzyv8q5NFInXnlFfm/fdZfx725z26LtxRdlozNgALB6teo0RE3n5QV88IE8wvaJJ1SnobN11VXApZcCkycDDz3E+yT1xMvkhTcufQNpBWl4ax1P/mmMSZOAgQPlaW28u82YNE0efLVhAzBoEJCaqjqR8ThsDhx9+yg0Xw0R4yJUxyEA4eHAa68Ba9YY/+42ty3aLrwQWL8eCA4GLrqIo3/kHvr1491tRmexAD/+KGdMX31VHjRTUqI6FVUb0X4Erux0JZ7/83leAdAIJpMcVOLdbcZ2yy3AL7/Ie2779wf+/FN1IuPIW5aH5HOSkTU3C9F3RMMryEt1JPrbLbe4x91tblu0AfLUmHXrgPPPB26+Wc5OGH1qlIh3txmflxcwc6YsvpcsAS64ADh8WHUqqvbs0GdRUlmCr3d9rTqKofDuNvcwdKjsO4WFAcOHcyn3mZTuKsX2UduxfeR2OMod6Da/GxLfTlQdi07iLne3uXXRBgChocDSpcDEifJ0q/HjeQAAGRvvbnMfkyfLoi0tTY5qr1+vOhEBQFZpFgCgc3hnxUmMh3e3uYfERFm4XXihPMhh+nQOev9TZVYl9t29Dxt7bkTRuiJ0eL0D+u/uj4ixEdA0TXU8+gd3uLvN7Ys2APDxkcs2XnsN+O47YMgQXh5JxjZ2LHDllby7zR1ccgmwdi0QECBHuL/6SnUiWnloJcyaGYPaDFIdxXB4d5v7CAmRg96TJsmDZq69FigtVZ1KPXu5HYdeOoT1ieuR+WEmYqbEYEDKAMT+OxYmH4/oVhuW0e9u85jvLk2TU6ILFwJ79shR7S28Q5UMqnrDOO9ucw9du8pZtn79gOuvl9c78O9UnZWHVqJ3dG+09G2pOooh8e429+HtLZeVvfEG8P33wODBnnslgBACWV9mYUPnDUibnobgi4LRb1c/JL6VCO8wb9XxqAGMfnebxxRt1a64Qp4maTLJfSQLFqhORHR24uKA557j3W3uIjxcHgBw663AU08BN90ElJWpTuV5ym3lWH90PYbED1EdxdB4d5v70DTgvvuARYtkEd6/P7Bpk+pUrlWwqgBbztuCPTfsgXeIN3r91gs9vu8BS0eL6mjUSEa+u83jijYA6NVLnrzXowcwbhzw3//yhwoZ09SpwLnn8u42d+HrC3z0kVyK9MUXwLBhxj7pyog2HN2ASnslBscPVh3F0Hh3m/sZPVoem+7tLfe6ffed6kTOV5RchG0jt2HrhVtRfqgcnT7qhD7JfRAyLER1NGoCo97d5pSiTdO0f2uatkvTtJ2apn2haZqfM57TFFFRwIoVcinSo48CEyZw0zQZT/XdbVlZvLutofTePmmaPJZ4/nxgxw551+T27apTeYZlKcswYeEE+Jp9cX7c+arjGB7vbmscvbdNgBzsXr9eDn5fcw3wwgvuOehdsrMEO8ftxOZ+m1GcXIz2r7THgJQBiL4tGpqZh4wYnVHvbmv2ok3TtBgA0wD0FUJ0B2AGcH1zP6c5+PsDn38OPP20PNJ2wgTViYgar2/fmrvbdu9WnUbfjNQ+jR0r70iy2eS1JenpqhO5r2PFxzD+2/EYOW8kvE3eWJa0DKH+oapjGd7Jd7c984zqNPpmpLYpMlIOet9wA/D443JGtT5lqcZa4209YMXum3YjuWcy8n/NR9tn2mJg6kDEPRgHs8WsOh41o5PvbisuVp2mYZy1PNILgL+maV4ALAB0e1ajpsn9I19+Kf/iiIxoxgy5tO7tt1UnMQTDtE+9ewMbNwIvvgi0aVP/xwl3HOp2AbvDjlnrZ6Hz252xcO9CPDfsOWy7exuGtOV+tubSowdw441y2W9Rkeo0umeYtsnPD5g3T+5dvOOOuj8m//d8bOi0ARkfZ7g23FkoP1yOvRP3YkOXDcj5Pgdxj8RhYNpAtJ3RFl6BvCTbHWma/NlaUGCcJdzNXrQJIY4CeBXAYQAZAAqFED//8+M0TZukaVqypmnJ2dnZzR2j0caPl9P9REYUFiZHPT/9lHvbTqch7ZPe2qbWreVMan2KK4px4UcX4qcDP7kulBtIPpaMAXMGYNrSaRgUOwg7J+/EE4OfgK+Xr+pobmfKFKCkRLZPVDcj9p2qDyhp1aruPw86LwjBQ4Oxb+I+5C7V5/pYW5ENKfenYH3iemR9loWYKTEYmDoQ7V9sD+9Qngjp7gYMAPr0kQPeRhj7dMbyyBAAYwC0A9AaQICmaUn//DghxAdCiL5CiL4RERHNHYPI40yZIu/Q+fhj1Un0qyHtk9HapsySTOSX5+Oyzy/DhIUTkF+WrzqSrhWWF2LqkqnoP7s/jhUfw1fXfIWlNy1FQmiC6mhuq18/eeKgUTpGKrhj38nkY0K377qhRY8W2HXNLhRv0s8aNCEEjn97HBu6bED6m+mIuiUKA1IGIPHNRPhE+qiORy6iabLvtHu3XPKrd85YHjkCQJoQIlsIUQVgPoDznPAcpxPCjqKiZNUxiBqkd29g0CC5t81IpyG5mNu0T9USwxKxedJmPHbBY/hs22fo9m43/LDvB9WxdEcIgS93fonO73TGOxvfwZT+U7Dnnj24rtt10DQeLOBsU6cC+/YBy5erTqJbbtc2AYBXoBd6LOkB73BvbB+9HWVp6ve4laWWYcfoHdh97W74RPqg97re6DS7E/xidXfuC7nA9dfL1UpG2F7ijKLtMICBmqZZNPmTcDiAPU54jtOlp7+JzZv7obycJwCQMUydChw4IO/7ojq5Tft0Ml8vX/xn+H+wfuJ6hFnCcOWXV+LmBTcjryxPdTRdSMlLwaVzL8UN392AmJYx2HDnBswcNRNBfkGqo3mMa68FIiKM0TFSxC3bJgDwjfZFz596QlQKbB+5HZU5lUpyOCodOPTiIWzsthGFfxYi4c0E9N7QG4H9A5XkIX3w8wPuvBNYuBA4fFh1mtNzxp629QC+BbAZwI6/n/FBcz/HFUJDRwMAcnMXKU5C1DBXXy1P9mLHqG7u1D7VpU/rPtg0aRNmDJ6BL3d+ia7vdMX3e79XHUuZksoSPP370+j+bnesS1+HWaNmYf3E9ejbuq/qaB7H11deAfDDD8DBg6rT6I+7t00BXQLQ44ceqDhcgZ1X7ITdanfp8wtWFiD5nGSkPZaG0NGh6L+3P9rc2wYmL4+8rpj+4e675fv331eb40yc8t0qhHhKCNFZCNFdCHGzEMKQN6AFBHSGv39H5OR4bqeHjMXHR14WuXgxkJqqOo0+uUv7VB8fsw+eGfYMNt65EdEtozH2q7G44bsbkGPNUR3NZarsVXg/+X0kzEzAM388gzGdx2DvlL2Y0n8KzCYe263K3XfLawDee091En1y97Yp6PwgdPm8C4rWF2H3jbsh7M7f4FiZXYm9E/Zi65CtcJQ50OPHHuj+bXf4xvDAIaoRHw9ceSUwezZQXq46Tf04xHAG4eFXoaBgBaqqClRHIWqQu+4CzGbg3XdVJyGVzok6BxsmbsCzQ5/Fd7u/Q9d3uuLb3d+qjuVUQggs2LMA3d/rjn8t/hcSwxKx5vY1+Oqar9C6ZWvV8Txemzby/sE5c4Ay9VubSIGIsRFImJmA3IW5ODD1gFOuK7EV2pD5aSa2X74da2PWImtuFuKmx6Hfrn4IGx3W7M8j9zB1KpCTA3z1leok9dP0cL9P3759RXKyPg/8KCxciy1bzkOXLp8jMvIG1XGIGmT8eODnn4GjRwGLRU0GTdM2CSEMvQ5Nz21TY+zI2oEJCydgU8YmXNP1Grxz2TtoFVDPOd0Gtfrwajy8/GGsObIGXcK74KURL+GKjlfwkBGd+eMPeaHthx8Ct9+uLgfbJ7X+evQvHPnvEQQOCoR3mDdMASaYLWaYLCaYA8wnfu0d5g3fWF/4xvrCL9YP5oC6Z8ptxTbk/pCL418dR97SPIhKAd84X7S6rhWi7ohCQOcAF3+FZDRCAN26yT7Txo3yZEkVTtc28cbAMwgMHABv70jk5HzPoo0MY+pU4Ouvgc8/ByZOVJ2GVOsR2QPrJq7Dq2texVO/P4UVaSvw9mVvY3y38YYvavbm7MWjyx/Fwn0LEd0iGrOvmI3bzrkNXib+eNOjwYOB7t2BWbOACRPUdYxIrfYvtIdm1lC4shAVRytgt9rhsDpgL5XvHeV1H4HsFep1ooDzjfWFb4wvijcXI29JHhzlDvjE+CDmnhhEXBeBwAGBhm/fyHWqj/+/5x5gwwZ5h5vecKatAfbtm4Tjx7/E+ednw2TiOmjSPyGAc8+V77duVdMx4ki2Pu3O3o3bF96O9UfXo0NIB/SM7IkerXqgR2QP9GjVAwmhCbrf9yWEwLr0dZi9eTY+3fYpLN4WPHL+I7hv4H0I8OGIut793//J/W2rVwPnKTrUnu2Tvgm7gN1qR1VOFSqOVKDiSAXKj5Sj4vBJvz5SAVueDT5RPoi4NgKtxrdC4KBAaCYWanR2iouBmBi5v23uXDUZONPWROHhY5CRMRv5+SsQFjZSdRyiM6oeMbrzTmDVKuDCC1UnIr3oGtEVq29fjdmbZ+PXtF+xI2sHFu5bCIeQI9t+Xn7oGtFVFnKteqB7q+7oEdkD0S2ilY9aHyk8gs+2f4ZPtn2C/bn7YfG2YHK/yXhy8JOICND3RcNUIykJeOQRecqtqqKN9E0za/Bq6QWvll7wb+df78fZrXaY/Ews1KhZtGwpVwC89x7w2mvyNG494UxbA9jt5Vi9OhyRkUno1Enn54ES/c1qlSNGl1yiZmMtR7KNo6yqDHty9mBH1g7sOP73W9YOZJRknPiYMP8w9IrqhYExAzEodhAGtRmEMIvzN/Vbq6xYsGcBPtn2CZanLoeAwOD4wbit1224pus1aOnb0ukZqPndf79cInn4MBAd7frns30iorrs2wd07gw89xzwxBOufz5n2prIbPZDWNgo5OYughDvQtN46Cbpn8UC3HEH8Oab8kCSmBjViUiv/L390Tu6N3pH9671+7nW3BMF3M7jO7EpYxP+u/q/sAt5x1LHsI4Y1EYWcOfFnoeuEV2bZWmlEAKrj6zGx1s/xte7vkZxZTHaBrfFjCEzcEuvW9A+pH2Tn0FqTZ4MvPEG8MEHwFNPqU5DRCR16iQHu997T64I8PZWnagGi7YGCgsbg+zsb1FcvBGBgTrcnUhUh8mTgddfl3tInn1WdRoymjBLGIa2HYqhbYee+D1rlRXJx5Kx9sharElfgyUHluCTbZ8AAFr6tMSANgNOFHEDYgYgxD+kztcWQiC/PB8HCw7iUMEhHCo8dOL91sytSCtIQ4B3AK7tdi1u7XUrBscPhokDZm4jIQEYNUpeZjt9urxjkohID6ZMkfvavv8euPZa1WlqsGhroLCw0QDMyMn5nkUbGUb79sDo0bJoe/xxwJfn6FATWbwtGBw/GIPjBwOQxVdqfirWHFmDtelrsTZ9Lf7z539O7JHrEt4Fg9oMQofQDkgvSq9VnJVUlpzy2vFB8ejeqjueGvIUru56NVr4tHD510iuMXUqcNllwIIF8poSIiI9uOwyoF07ue+WRZsBeXuHIDh4KHJyFqJ9+xdVxyFqsClTgJEjge++A268UXUacjeapqFDaAd0CO2Am3vdDAAoqSzBhqMbsPaILOK+3/c98sryEOIXgvjgeCSEJmB4u+FoG9wW8cHxiA+KR3xwPML8w5QfdkKuc+mlQIcOsmPEoo2I9MJsliuVHnoI2L4d6NlTdSKJRVsjhIePQUrKNFit+2CxdFIdh6hBLr4YSEyUy5BYtJErtPBpgYvaXYSL2l0EQM7GWausPI6fajGZ5J1I998P7Nwp728jItKD228HnnxSrlR65x3VaSRuEGiE8PAxAICcnIWKkxA1nMkE3HYb8OefwMGDqtOQJ9I0jQUb1SkpSY5qz5unOgkRUY3QUOCqq+Tp25WVqtNILNoawc8vDi1a9GbRRoZTPcP2+edqcxARnSwiQi6TnDcPcDhUpyEiqpGUBOTmAsuWqU4isWhrpPDwMSgqWovi4k2qoxA1WNu28oLtzz4DdHA1IxHRCUlJwJEjcjUAEZFeXHIJEB4OzJ2rOonEoq2RoqJug49PNDZvPg9Hj74DPVxOTtQQN90E7N0LbNmiOgkRUY0xY4AWLfTTMSIiAuQdbePHA4sWAYWFqtOwaGs0P7849O27FSEhI3DgwBTs2nU1qqryVcciOqNrr5UNEDtGRKQnFgswbhzwzTdAebnqNERENZKSZLs0f77qJCzazoqPTwR69PgBHTq8itzcH5CcfA4KC9eqjkV0WqGh8s62L74A7HbVaYiIaiQlyZHsxYtVJyEiqjFggLyaRA8D3izazpKmmRAb+wDOPXc1NM2MLVsuRF7ez6pjEZ1WUhKQmQn89pvqJERENS66CIiK0kfHiIiomqbJvtOKFcDRo2qzsGhrosDA/ujbdwv8/ROwf/9k2O1c20H6NXo0EBTEjhER6YvZLE+5XbwYyMtTnYaIqMZNN8lD3L74Qm0OFm3NwMsrCImJs1Be/heOHHlVdRyievn5yb1t8+cDpaWq0xAR1UhKAqqq5N42IiK9SEyUyyRVD3izaGsmoaEXIyLiGhw+/ALKyw+pjkNUr6QkoKREnoZERKQX55wDdO2qvmNERPRPSUnAtm3Ajh3qMrBoa0YdOrwOQENKyr9VRyGq14UXArGx7BgRkb5U7x1ZtQpIS1Odhoioxvjxchn3vHnqMrBoa0Z+frGIj38COTkLkJu7VHUcojqZTHJ99rJlwPHjqtMQEdW48Ub5/vPP1eYgIjpZRAQwcqQs2hwONRlYtDWz2Nj74e+fiJSUqXA4KlTHIapTUpI89v+rr1QnISKqER8vVwPMnSs3/hMR6UVSEpCeDqxcqeb5LNqamcnki8TEWSgrS8GRI6+pjkNUp27d5P4RLpEkIr1JSgL27gU2b1adhIioxpVXAi1aqOs7sWhzgtDQSxEePhaHDj2P8vLDquMQ1SkpCdiwAdi/X3USIqIa114L+PhwUImI9MViAa6+Wp5wW67ghi8WbU6SkPAGACAl5X7FSYjqdsMNcuO/yk21RET/FBIi75T84gvAZlOdhoioRlISUFQE/Pij65/Nos1J/PziERc3HTk536GwcLXqOESnaN0aGD6ce0eISH+SkoCsLOC331QnISKqMWwYEB2tZiUAizYnio29H97ekUhNfQyCvWLSoaQkIDUVWLdOdRIiohqXXQYEB3OJJBHpi9ksT7ldsgTIy3Pts1m0OZHZHID4+CdQWLgSeXnLVMchOsXYsYC/P5dIEpG++PnJvW3z5wOlparTEBHVSEoCqqrk3jZX8nLt4zxP69aTkJ7+GtLSHkNo6CXQNNbJpB+BgcCzzwIdO6pOQkRU2513ArGx3NdGRPrSqxfw0EPyvSuxaHMyk8kHbds+g717b0V29ndo1epa1ZGIannwQdUJiIhO1a+ffCMi0hNNA15+2fXP5bSPC0RG3gSLpRvS0p6Ew8EhQyIiIiIiajgWbS6gaWa0a/c8ysr2ITv7K9VxiIiIiIjIQFi0uUh4+BiYzYEoLFyjOgoRERERERkIizYX0TQNAQFdYbXuVh2FiIiIiIgMhEWbC1ksXVFayqKNiIiIiIgajkWbCwUEdEVV1XFUVuaojkJERERERAbBos2FLJZuAMAlkkRERERE1GAs2lwoIKArAHCJJBERERERNRiLNhfy9Y2F2dyCM21ERERERNRgLNpcSNM0WCxdUFq6S3UUIiIiIiIyCBZtLtayZR8UF2+Aw2FTHYWIiEjXbA4b5myeg62ZW1VHISKq5fjXx7E+cT0qMitc8jwWbS4WHDwUdnsJSkq2qI5CRESka3aHHXf+cCeWHFiiOgoRUS22IhvKUsogqoRLnseizcWCgoYAAAoKflcbhOgkGRkfIi9vueoYRES1mE1mALJ4IyLSE82kyV+4pmZj0eZqvr5R8PfvhIKCP1RHITohLe0pHD/+heoYRES1mDTZTXEIh+IkRET/UF2zOTjT5raCg4egsPBPCMGRQ9IHTTPz+5GIdKe6aLOzfSIineFMmweQ+9qKUFLCjdWkD5rmBYCdIiLSH7Nm5vJIItKfv2s2uGghAIs2BYKDq/e1cYkk6YOcaeOJpkSkP2aTmTNtRKQ/f1dRQnB5pNvy9W0Ni6UbcnIWqY5CBIDLI4lIvzjTRkR6pGl/T7Vxps29tWo1HoWFK1FRcVR1FCIALNqISJ8400ZEulRdRXFPm3tr1Wo8AIHjx79WHYUImubFoo2IdIkzbUSkS+5weqSmacGapn2radpeTdP2aJo2yBnPMTKLpSNatOiN48e/VB2FyKP2tLF9IjIWT5lpY9tEZCzucnrkWwCWCiE6A+gFYI+TnmNorVpdj+LiDSgrS1UdhTycppnhQadHsn0iMhAPmmlj20RkJEafadM0LQjAYAAfAoAQolIIUdDcz3EHcokkONtGynnKQSRsn4iMxxNm2tg2ERmPO8y0tQOQDeAjTdO2aJo2R9O0ACc8x/D8/OIQGHg+izZSzoP2tLF9IjIYD5lpY9tEZDRucE+bF4DeAN4TQpwLoBTAo//8IE3TJmmalqxpWnJ2drYTYhhDRMQ1KC3dgbKyv1RHIY/mMXvaztg+sW0i0hdPmGkD+05ExuMG97SlA0gXQqz/+7+/hWyIahFCfCCE6CuE6BsREeGEGMZQWroDJpMFXl5hqqOQB/OU5ZFoQPvEtolIX8yaRxRt7DsRGcyJ5ZFGnWkTQmQCOKJpWqe/f2s4gN3N/Rx3UFmZg6yseYiKugXe3sGq45AH85SDSNg+ERmP2eT+yyPZNhEZUPXySBftafNy0utOBTBP0zQfAKkAJjjpOYaWkTEbQlQgJmaq6ijk4TxoTxvA9onIUDxkpg1g20RkKNUzba46PdIpRZsQYiuAvs54bXeSm7sYgYEDERDQVXUU8nCedE8b2yciYzGbzHAIF60/UohtE5HBuHimzVn3tFEDlJUdQEBAd9UxiCAPIvGIkWwiMhgPOT2SiIym+iASo97TRg1jsxWhquo4/P0TVEch8qSDSIjIYDzk9EgiMhhNM/49bdQAZWUpAAB//0TFSYjknjZPOIiEiIzHpJk400ZE+lNdRRn19EhqmJqijTNtpJ4n7WkjImPxoINIiMhIqifauDzSvZWVHQAA+Pt3UJyEiMsjiUi/iiqKEOAdoDoGEVEtDqucYjP5uKacYtGmiNV6AD4+rWE28wcR6QGLNiLSH5vDhtT8VCSEclUKEemLdZ8VAODf0d8lz2PRpkhZWQr3s5FueNg9bURkEEcKj6DKUYXEUP68JCJ9se61wjvSG94h3i55Hos2RcrKDnA/G+kG97QRkR4dyJNbCTjTRkR6Y91rhaWzxWXPY9GmgN1eDrPZAoulk+ooRABk0cbTI4lIb1Ly5KFdiWGcaSMi/RBCwLrHtUWbl8ueRCeYzX4YODBNdQyiE3gQCRHp0YHcA7B4WxDdIlp1FCKiE6qyq2DLtyGgi+vOpuBMGxHB4aj4+642IiL9SMlPQUJoQs0ltkREOmDdKw8h4fJIInKp0tJdsFi6qI5BRFTLgdwD3M9GRLpj3cOijYhcTAgHSkt3oEWLnqqjEBGdUH3cP0+OJCK9se61wmQxwTfW12XPZNFG5OHKyw/Bbi9GQACLNiLSDx73T0R6Zd1rhaWTBZrJdUu3WbQRebjS0u0AwJk2ItIVHvdPRHpVuqfUpUsjARZtRB6vpGQ7AA0WSzfVUYiITuBx/0SkR3arHRWHKmDpwqKNiFyotHQH/Pzaw8urheooREQn8Lh/ItIj637XH0ICsGgj8nglJdu5NJKIdOev/L/QIaQDj/snIl1RcXIkwKKNyKPZ7VaUlR3gISREpDsF5QUIt4SrjkFEVIt1rxUwAf6J/i59Los2Ig9WWrobgIMzbUSkOyWVJWjhw2XbRKQv1r1W+LX1g9nP7NLnsmgj8mDVJ0dypo2I9KaksgQBPgGqYxAR1VKVXQXf1q67n60aizYiD1ZSsh0mkwX+/u1VRyEiqqWksgQtvDnTRkT6YiuywRzk2lk2gEUbkUcrLd2OgIAe0DQ2BUSkL6VVpVweSUS6Yy+0wyvQy+XPZU+NyEMJIXhyJBHpkhCCe9qISJdsRTaYAznTRkQuUlWVC5stFxZLV9VRiIhqKbeVwyEcLNqISHfsRZxpIyIXqqhIBwD4+cUqTkJEVFtJZQkA8CASItIVR6UDjnIHZ9qIyHUqK48CAHx8YhQnISKqrbSqFAA400ZEumIvtgMAZ9qIyHUqKmTR5uvLoo2I9KV6po1FGxHpia3IBgCcaSMi15FFmwYfnyjVUYiIamHRRkR6ZC/6e6YtiDNtROQiFRVH4eMTCZPJW3UUIqJaWLQRkR5Vz7RxeSQRuUxl5VHuZyMiXTpxEIk3DyIhIv2onmnj8kgicpmKiqPcz0ZEulRayYNIiEh/bIWcaSMiF2PRRkR6xeWRRKRHPIiEiFzKbi+DzZbHoo2IdIlFGxHp0YmDSDjTRkSuUFl5DADvaCMifaou2izeFsVJiIhq2IpsgAkwWVxfQrFoI/JAvKONiPSspLIE/l7+MJtcvwSJiKg+9iI7vAK9oGmay5/Noo3IA7FoIyI9K60q5dJIItIdW5EN5iA1g0ks2og8UE3R1kZxEiKiU5VUlrBoIyLdqZ5pU4FFG5EHqqw8CrO5Bby8AlVHISI6BYs2ItIjW5FNycmRAIs2Io9UUcGLtYlIv9IK0tAqoJXqGEREtdgLOdNGRC7EO9qISK8ySzKxNXMrRrQfoToKEVEtnGkjIpdi0UZEerUsZRkAYGTCSMVJiIhq4542InIZIRyorGTRRkT6tPSvpYhqEYVekb1URyEiqoUzbUTkMlVV2RDCxj1tRKQ7docdP//1My7tcKmSe5CIiOpTcbQCDqsDvq19lTw9QKQ6AAAgAElEQVSfRRuRhykr+wsAj/snIv1JPpaMvLI8Lo0kIt3JXZILAAi5JETJ81m0EXmY48e/hKb5IDh4sOooRES1LE1ZCg0aLm5/seooRES15C3Jg2+cLwK6BSh5Pos2Ig/icFQgK2sewsOvgrd3qOo4RES1LP1rKfrH9EeYJUx1FCKiExwVDuQvz0fYZWHKlm6zaCPyILm5P8Jmy0NU1ATVUYiIasm15mJ9+noujSQi3SlcVQh7iR2hl6kb8GbRRuRBMjI+go9Pa4SGcukREenLL6m/QECwaCMi3cldkgvNV0PIRWr2swEs2og8RkVFBvLyfkJU1C3QNDXH1RIR1WdpylKE+IWgX+t+qqMQEdWSuzgXwUODYQ5Q139i0UbkIbKyPgPg4NJIItIdh3BgacpSXNLhEphNHFQiIv0o+6sMZfvKEHaZ2r22LNqIPIAQApmZHyEw8DxYLB1VxyEiqmV71nZklWZhVMIo1VGIiGrJ/Uke9a9yPxvAoo3IIxQXb4DVupezbESkS6sOrwIADGs3THESIqLa8pbkwb+jPywJFqU5nFa0aZpm1jRti6ZpPzrrGUTUMBkZH8Fk8kerVtepjqILbJ+I9CX5WDIiAyIRGxirOopSbJuI9MVutaNgRYHypZGAc2fa7gWwx4mvT0QNYLeX4fjxLxERcQ28vAJVx9ELtk9EOrLx2Eb0bd1X2f1HOsK2iUhHClYUwFHuUL40EnBS0aZpWhsAowHMccbrE1HD5eQsgN1eyKWRf2P7RKQvJZUl2JO9B31b91UdRSm2TUT6k7skF6YAE4IHB6uO4rSZtjcBPAzAUd8HaJo2SdO0ZE3TkrOzs50Ug4gyMz+Cn19bBAcPUR1FL07bPrFtInKtLRlbICB41D/7TkS6k7csDyHDQ2DyVX8MSLMn0DTtcgDHhRCbTvdxQogPhBB9hRB9IyIimjsGEQEoLz+M/PxfERl5KzRNfYOjWkPaJ7ZNRK618dhGAECf1n0UJ1GHfSci/bGX2lH+VzkCB+hja4kzenHnA7hS07SDAL4EcJGmaXOd8BwiOoPs7G8ACERF3ao6il6wfSLSmeRjyWgT2AZRLaJUR1GJbRORzlj3WwEA/h39FSeRmr1oE0JMF0K0EUK0BXA9gN+EEEnN/RwiOrO8vGWwWLrB37+d6ii6wPaJSH+SjyV7/NJItk1E+lO2vwwAYOmk9qj/alwvReSm7HYrCgpWIjT0UtVRiIjqVFBegAN5Bzz+EBIi0h/rPiugAf4J+php83LmiwshfgfwuzOfQUR1KyhYCSEqWLTVg+0TkXqbjsktXCzaarBtItIH6z4rfON8YfY3q44CgDNtRG4rP38ZTCY/BAVdqDoKEVGdko8lA2DRRkT6U7a/TDdLIwEWbURuKy9vGYKChsBs1se0PhHRPyVnJKN9SHuE+qu/uJaIqJoQAtZ9VhZtRORc5eVHYLXu4dJIItK1jUc3cpaNiHSnMrMS9mK7bk6OBFi0EbmlvLxlAIDQ0EsUJyEiqlt2aTYOFR7y+JMjiUh/rPvkcf+caSMip8rPXwYfnxhYLF1VRyEiqtOmDB5CQkT6dOK4/44s2ojISRwOG/LzlyM09FJomqY6DhFRnTYe3QgNGnpH91YdhYioFus+K0z+JvjG+qqOcgKLNiI3U1y8ETZbAfezEZGuJWcko1N4JwT6BqqOQkRUi3WfFf6J/tBM+hn8ZtFG5GbkfjYTQkJGqI5CRFSv5GPJXBpJRLpUtr9MV0sjARZtRG4nP38ZWrbsB29vHqFNRPp0rPgYjhUfQ99oFm1EpC+OSgfKUsvg30k/J0cCLNqI3EpVVT6KijZwaSQR6dr/tvwPADCk7RDFSYiIaitLLQPs+jo5EmDRRuRW8vOXA3CwaCMi3cosycRLq17C1V2uxjlR56iOQ0RUix5PjgRYtBG5lby8ZTCbg9CyZX/VUYiI6vT070+jwl6Bl0a8pDoKEdEpqu9o09PF2gCLNiK3IYRAfv4yhISMgMnkpToOEdEpdmfvxuzNs3FPv3uQEJqgOg4R0Sms+6zwjvCGd4i36ii1sGgjchNW6x5UVKRzaSQR6dbDvzyMlj4t8eTgJ1VHISKqU8mmEli66GtpJMCijchtyKP+waKNiHTp19RfsfjAYjwx+AmEWcJUxyEiOkXJ9hKUbC1BxLgI1VFOwaKNyE3k5S2DxdIZfn5xqqMQEdXiEA48+MuDaBvcFlP6T1Edh4ioThkfZkDz0RCZFKk6yilYtBG5gYqKTBQU/I7Q0JGqoxARnWLu9rnYmrkVLw5/EX5efqrjEBGdwlHhQNbcLIRfFQ7vMH3tZwNYtBG5hcOHX4IQNrRuPVl1FCKiWqxVVjz+2+PoH9Mf47uNVx2HiKhOOd/nwJZnQ/Qd0aqj1IlHzBEZXHl5Oo4dex9RUbfBYklUHYeIqJY3172J9KJ0fD7uc2iapjoOEVGdMj7MgG+cL0JGhKiOUifOtBEZ3OHD/wHgQNu2PI2NiPQlqyQLL656EWM7j8WF8ReqjkNEVKfyQ+XIX56PqAlR0Ez6HFxi0UZkYGVlacjImIPo6Dvh5xevOg4RUS3P/PEMym3lvEibiHQt8+NMAED0BH0ujQRYtBEZ2qFDz0LTvBAf/7jqKEREtRwtOooPNn2Au/vcjY5hHVXHIQ8gHEJ1BDIg4RDI+CgDISNC4Bev34OSWLQRGZTVuh+ZmZ+idevJ8PVtrToOEVEtC/YugF3YecQ/uUz6m+nY1G8T0t9OR1Vuleo4ZBD5v+aj4lCFbg8gqcaijcigDh58GiaTP+LiHlEdhYjoFPP3zEfXiK7oFN5JdRTyED7RPnBUOZAyNQVrotdg59U7UXawTHUs0rmMDzPgFeqF8KvCVUc5LRZtRAZUUrITx49/iTZtpsHHp5XqOEREteRYc/DHoT8wrvM41VHIg0TeEIl+W/uh79a+iJkSg/zl+dg2fBsqjlaojkY6VZVbhZwFOYhMioTJV99lkb7TEVGdDh58CmZzS8TGPqg6ChHRKRbtWwSHcGBsl7Gqo5AHatGrBRJeT0CvX3qh6ngVto3YhsrsStWxSIey52dDVApETYhSHeWMWLQRGUxx8Sbk5MxHbOwD8PYOVR2HiOgU8/fMR3xQPM6NOld1FPJggf0D0WNxD5QfKse2i7ehKp/73Ki2ghUF8InyQYteLVRHOSMWbUQGk5Y2A15eoWjT5j7VUYiITlFcUYxfUn/BuC7jeJk2KRc8OBjdF3SHdbcV20dth63YpjoS6YQQAgV/FCBoSJAh2ioWbUQGUli4Fnl5SxAX9zC8vAJVxyEiOsWSA0tQaa/EuC7cz0b6EHppKLp+3RXFycXYccUO2K121ZFIB8pTy1F5rBLBQ4JVR2kQFm1EBpKW9iS8vVshJoZHaBORPs3fOx+RAZEY1GaQ6ihEJ0RcFYEun3ZB4cpC7Lp6FxwVDtWRSLGCPwoAgEUbETWv4uJNKCj4FXFxj8JsDlAdh4joFOW2cizevxhXdb4KZpNZdRyiWiJvjETHDzoib2keDkw7oDoOKVbwRwG8I7xh6WJRHaVBWLQZTGVlNux2q+oYpEBOzvcAzIiKulV1FCKiOv3y1y8orSrl0kjSrdYTWyP24VhkfJCB7AXZquOQQgV/FCBosDH2swEs2gwnNXU61q6NRWrqdJSXH1Edh1woJ+cHBAWdzxMjiUi35u+dj2C/YAxtO1R1FKJ6tXuuHVr0boF9E/eh4hjvcPNE5YfKUXGowjBLIwEWbYYTFXUbgoOH4vDhl7FuXTvs2nUdCgpWQQihOho5UXn5IZSWbkN4+JWqoxAR1cnmsGHRvkW4vOPl8DH7qI5DVC+TjwldP+8KR7kDe27ZA+FgH8rTGG0/G8CizXCCgy9A9+7fYeDAVMTG3o/8/F+wdeuF2Lv3Vtjt5arjkZPk5v4IAAgLu0JxEiKiuq08tBJ5ZXkY15lLI0n/LJ0sSHgzAQW/FiD9jXTVccjFCv4ogFeoFwK6G+eMABZtBuXnF48OHV7GoEHpiI9/CllZn2Hr1sGoqDiqOho5QU7OIvj7d4LF0lF1FCJDqLJXYdG+RapjeJT5e+bD38sflyZcqjoKUYNET4xG+FXhSJ2eiuItxarjkAsV/FGAoAuDoJmMsZ8NYNFmeGZzANq1exrdu38Pq3UPNm3qh8LCdapjUTOy2YpQULAC4eGcZSNqqDmb52DMl2MwYeEElFaWqo7j9hzCgQV7F2BU4ihYvI1xEhuRpmnoOLsjvMO9sefGPby/zUNUHK1A+V/lhloaCbBocxvh4WNw7rlrYTL5Y+vWIcjM/ER1JGomeXk/Q4gqhIVxPxtRQ03qMwkzBs/AJ1s/+f/27jw+qvLe4/jnmclMVjKBBMJOWASLgKKiqLjv4o629SrXraJWbbW21Wq12tqK2lv13utytWoXpa6oWPdaRXFpQVEWEWSRTbaENSQh23P/OAnrhHUmzzlnvu/XK68ko6/MN2Hyy/M7z3I46I8HMX35dNeRQu3fi//Nt+u+1dJICZx4SZy9/7I3VV9VMef6Oa7jSCsI4n42UNMWKgUFAzjggH+TSAzjq68uYvbsn9DYWO86luyhiopxZGW1o7BQN6oV2VnRSJTbj76dt0a+RXlVOUMeHcITk59wHSu0xs4YSywSY3jf4a6jiOyydse1o+v1Xfn24W8pH1fuOo6k2erxq4kWRinYt8B1lF2S5TpAmFgLdXVQVQXV1d7bjj6+8EIoLExdhlismEGD3mTOnOtZtOhe1q+fRv/+zxCLtU3dk0iraWysp6LiNYqLhxOJ6NdVdl9Dw87XpepqGDgQhg1znXrPHdfrOD6//HPOH3s+l4y7hFkVs/jdsb8LzH15gsBay9gZYzm217EU5QTryrW4Zy1s2LDztam+Hq68MvU5ev22F6veXsWsK2aROCJBrCiW+icRX1g9fjWJYQlMNFh/BzQKbMHChTBrFqxeDWvWbPm+pY/XroXGxl17nhNPTG3TBhCJZLHXXvdTUDCIWbOuZMaM8xk48FUNUgJo7dqPqa+v0KmRstGGDTBx4vZrUbK6tWEXb0X04x+Ho2kD6NSmE2+PfJurXruK0R+OpryqnIdPfZhoJOo6WuBZa3l55svMWTWHGw67wXUccWzmTJg/f/u1aOuPKyu9xm1nxePpadoi2RH6/bEfnw39jLk3zqXfw/1S/yTi3IalG6ieWU2nSzq5jrLL1LS1YN99YdWqbR9PJLy3oiLvrXt3730i4TVfeXmQm7vt+5Y+bpvGCbBOnS6loaGK2bN/xNKlT9Cp0yXpezJJi4qKVzAmRrt2Oo1NPL/+Nfzud9s+npOzqRYVFXm1paxs02P5+TuuR5t/nOqLSa5FI1EeGv4Q7fPac8cHd7CyZiVPnf0UOVk5rqMFUkNjAy999RJ3fXgXE7+dSLfCbpz1nbNcxxKHFi6Evffe9vFIZMtxUyIBvXtv+rhNm+Q1qKUalZubvu+hcEghXa/tyqI/LKL0P0opOkIzx2Gz5v01QPD2s4GatqQaGryG7dJL4Zprtiws0YBdmO3S5SpWrHiB2bOvo23b48nJ6eY6kuyC8vJxFBUdRVZWyEbQstvKy72G7M03Nw2EEgnIznadzP+MMfzmmN9QnFfMdW9ex/Axw3npey/RJruN62iBUVNfw1+/+Cv3fHQPX6/8mt5te/PQ8Ie4cN8LyY2lcTQtvrdypff+zjvh1FM31aeCAgjSQp+ev+5J+dhyZl42kwO/OJBoTsAGfrJdq8evJpIfoWD/YO1nAx1EklRdnfe+d29vxq1HD6/wBK1hAzAmwt57P4619cyceRl2V9YgiFNVVbOorp6ppZGyhdpab9ZsyBDo2xc6dFDDtquuHXotfznzL4z/ZjzH/OUYyqt08MCO1DXUcdeEu+h5f09G/X0UhdmFPHvOs8y8eiZXHHiFGjahttZ7P2CA99atm3exO0gNG0A0P0rf/+tL9axq5t8x33UcSbHV41eTOCxBJBa8Fih4iVtBc9MWj7vNkSq5ub3o1esuVq16k6VLH3cdR3ZSRcUrAGraZAt1deGpTS6N3HckL37vRaYtn8awx4exYM0C15F87d1v3uXGd26kX3E//jHyH0y8bCLn7nOu9gXKRmEaO7U7oR2l/1nKwrsWUjml0nUcSZHa8lqqplcFcmkkqGlLqvlqUSxEBwd16fJDioqOYvbsn1BTs9B1HNkJ5eWvkJ8/kNzcMtdRxEdqa8NVm1w6rd9pvHXBWyypXMJhjx/GjBUzXEfyreyoN51765G3cmyvY3WwlWwjbGOnPn/oQ1bbLGZeNhPboFVKYRDk/Wygpi2p5sIThqtFzYyJ0K/f41jbwMyZP9AySZ+rq1vJmjUTdENt2YZm2lLr8B6HM/6i8dQ11HH4E4czcfFE15F8KZGTAGBNzRrHScSvwjZ2ihXH6HNfH9b9ex2L/3ex6ziSAqvHryaSG6HNkGDuY1bTlkSYpvg3l5vbk96972bVqrdYsuSPruPIdqxc+TrQQEmJlkbKlmprw1ebXNuv4358eMmHFGYXcvSfj+Yfc//hOpLvJLKbmrYNatokuTCOnTqc14F2J7dj7s1zqVlQ4zqO7IH1M9ZT/lI5hYcUEokHs/0JZuo0C9sU/+Y6d76CoqKjmTPnempqtIfDL9auncSSJU+wcOG9zJt3GwsX/p5YrJQ2bYa4jiY+U1cXztrkWu92vZlwyQR6tu3J8DHDmbNyjutIvlKY7Z1gq5k2aUkYx07GGPr8dx8a1zdS/qIOLAqihpoG5v1qHpP2nUTDuga639jddaTdpiP/kwjj1aJm3jLJx5g4cSAzZ/6AQYPe1N4EH5gy5Xjq61dv/DwabUO3btdjjK6ryJY005Y+ndt0ZszZYxj08CA+WfQJvdv1dh3JNzY2bZppkxaEdeyU2zuXSF6EmvmaaQuaVe+tYtbls6ieVU2H/+hAn3v7EO8Q3BeomrYkwni1aHPeMsl7+PrrH7JkyaN07jzKdaSMl53dlYKCweyzzwtkZRVijE5kk+Tq6tJ7c9lM17e4LwbDrIpZrqP4SiwaIy+Wp5k2aVFYx07GGHLKcqj5Rk1bkMy9aS4L7lxATs8cBr0xiHYntnMdaY/pMn4SYb1atLnOnS+nqOgY5sy5ng0bvnUdJ+Pl5w+gpmYesVhbNWyyXZppS6/srGzKisqYtVJN29YS2QnWbljrOob4VJjHTmragqfi1QoK9i9gyLQhoWjYQE1bUmE7ASkZYyL07fswDQ2VLF36J9dxMl5+/kBqar6hvn6d6yjiczo9Mv36lfRjZvlM1zF8J5GT0PJIaVGYx05q2oIn3iFOJB4hmheeC+Epb9qMMd2MMe8aY740xkw3xvw41c+RbmGd4t9aXt5eJBKHs2zZX3ULAMfy8wcAsH79NMdJwi0s9Snstcm1vu36MqtiluriVgqzC9W0pUlYahOEsz7l9MihflU99WvqXUeRnRQrjVG7rNZ1jJRKx0xbPXC9tbY/MBS4yhjTPw3PkzZhnuLfWmnpSKqqvmLdukmuo2S0/PyBgJq2VhCK+pQJtcmlfiX9WF+3niWVS1xH8ZVEdkJ72tInFLUJwlmfcspyAHQYSYDEO8TVtO2ItXaJtfazpo/XATOALql+nnQK89WirbVvfy7GZLNs2V9dR8loOTk9iEYLWL9+qusooRaW+pQJtcmlvsV9AXQYyVa0PDJ9wlKbIJz1aWPTpiWSgREvjdNY1UjD+gbXUVImrXvajDFlwGDgX0n+2yhjzCRjzKQVK1akM8Yua2j6942GZxlsi2KxIkpKTmP58qdpbKxzHSdjGRMhL28fzbS1opbqk59rE3j1KRNqk0vNTZv2tW1JB5G0Do2d/EczbcETK/WuHoRpti1tTZsxpgB4AbjWWrtNlbfWPmKtPdBae2D79u3TFWO3NG9jyJTbl5WWjqSubgUrV77pOkpGKygYyPr1U7WPphVsrz75uTaBV58ypTa50rWwK7lZuZpp24qWR6afxk7+FGsfI5Ib0UxbgDTfj01N2w4YY2J4Recpa+3YdDxHawhj4UmmXbuTiMVKtETSsfz8AdTVlVNXt9x1lFALen1S05Z+ERNhr+K9dOz/VgqzC1lft576Rh3GkA5Br03NwlifdK+24ImXqmnbIWOMAR4DZlhr/5Dqr98aMm2iIxKJ06HD9ykvf5m6utWu42Ss5sNIKiu1ry1dwlKfwjgo8pu+xX21PHIriZwEgJZIpkFYalOYqWkLlublkXXLw7P1Jx0zbYcBI4FjjDGfN72dkobnSZswT/G3pLR0JNZuYMWK511HyVibjv1X05ZGoahPmVSbXOlX3I+5q+ZS1xCeP/h7KpHtNW1aIpkWoahNEN76lFOWQ808NW1BEW8fvpm2rFR/QWvtBCDQv7JhLzzJtGkzhNzcvixb9lc6d/6B6zgZKR7vQCzWQYeRpFFY6lMm1SZX2ue1p8E2UFlbSdvctq7j+ELzTJtOkEy9sNQmCG99inWIUb+qHttgMdGQfpMhEsmOkFWUFaqmLa2nRwZV2AtPMsYYSktHsmbN+1RXf+M6TsbKzx+omTbZLjVtrSM3lgtAVV2V4yT+0TzTpuWRkkzYx05Zbbx5jjAdIR92sdKYlkeGXdgLT0tKSy8AYPnypxwnyVz5+QNYv3461ja6jiI+paatdeRmeU1bdX214yT+UZhdCGh5pCQX9rFTtMC7l0HDOjVtQRG2G2yraUsi7IWnJbm5ZSQSR7Bs2RjXUTJWQcFAGhurqKmZ5zqK+JSattaRF8sDoLpOTVszLY+U7Qn7QSTRNl7TVr9Op6cGRbxUTVvoZWrTBlBUdARVVV9hra4kubDpMBLta5Pk1LS1Di2P3JYOIpHtCXttam7aGio1PgoKLY/MAJnctMXjXYBGamuXuY6SkfLy9gF07L+0LOwDI7/Q8shtaaZNtifstUnLI4MnXhqnflU9jbXh2HKipi2JTG7asrM7A7Bhw2LHSTJTVlYBOTk9dRiJtCjsAyO/0PLIbeVk5RCPxjXTJkmFvTZtnGlT0xYY8Q5Nx/4vD8cSSTVtSWR209YFgNrabx0nyVzeCZJaHinJhX1g5BdaHplcYXahTo+UpMJemzaeHqnlkYERthtsq2lLorFpFjWSgT+deFwzba7l5w+kqmomjY0bXEcRH2pszMza1Nq0PDK5RHZCyyMlqbDXJi2PDJ54abhusB3iX6/d19D0+xiNus3hQjzeAYiyYYNm2lzxDiNpoKpqpuso4kMNDZlZm1qblkcml8hR0ybJhb026fTI4Nm4PFJNW3hlctNmTJR4vCO1tZppc6WgYCCA9rVJUmEfGPmFlkcml8hOaE+bJBX22qSZtuDR8sgMkMlNG3j72jTT5k5ubl+MiWlfmyQV9oGRX0SN90Ouqa9xnMRfNNMmLQl7bTIRQyQ/oj1tAZJVkEUkL6KZtjBT09ZZe9ocikRi5OXtrWP/JamwD4z8YszUMQAM7TrUcRJ/0UEk0pJMqE3Rgqhm2gIm3iE8N9hW05ZEpjdt8XgXnR7pWH7+AC2PlG1Y671lam1qLfWN9dzz0T0M7TqUI3oc4TqOr2h5pLQkY5o2zbQFSqw0Rt0yLY8MrUxv2rKzO1Nfv4qGBm3AdyU/fyAbNiygvl5XtGWTTK9NreW56c8xb/U8bjzsRkyYzzDfDYnsBGs3rKXRhuNmtZI6mdC00QgmqpoQJPHSuO7TFmaZPjDSvdrcy89vPoxE+9pkk0yvTa3BWsvoD0fTv31/Tut3mus4vpPISWCxVNZWuo4iPpMJTVtjTSORHA2dg0TLI0Mu0wdGulebe96x/2raZEuZXptawxuz32DKsinccNgNRIz+RG4tkZ0A0BJJ2UZGNG3VjURyVReCJFYao25FHbbBuo6yx/TKSyLTB0bZ2c1Nm2baXMnJ6UE0WqB9bbKFTK9NrWH0h6PpVtiN8wac5zqKLxVmFwLoBEnZRkY0bZppC5x4aRwaoW5l8Pe16ZWXRKYPjBobvWnkSCTbcZLMZYxpOoxEM22ySabXpnT7aOFHvD//fX566E+JRWOu4/hSIsebadMJkrK1sDdt1lqvadNMW6CE6QbbeuUlkekDo9rapQDE4x0dJ8ls+fkDqaycirXBn9KX1GiuTRFV7rS468O7KM4t5tLBl7qO4ltaHiktCXvT1rjBO3xHM23BsvEG2yE4QVKvvCTUtKlp84P8/AHU11ds/PcQyfTalE7Tl09n3Mxx/OjgH5Efz3cdx7fa57dn39J9iUfjrqOIz4S+aatuato00xYo8dKmmbYQnCCZ5TqAH2X61eza2mUAxOOljpNkts1PkMzO7uQ4jfiBmrb0ufuju8mP5XPVkKtcR/G1Pu368PkVn7uOIT4U+qatRjNtQaTlkSEX9sKzI7W1S4lG2xCN5rmOktE2nSCpw0jEo6YtPeavns+YqWMYdcAoivOKXccRCaSwj52aZ9qiuSH+JkMoq20WJstoeWRYNTaCMZCpW4lqa5dqls0H4vH2xGKlOoxENmpsup+x7vecWn/4+A8YDD855Ceuo4gEVvPYKaw00xZMJmKIdYhRu0IzbaHUty/U18Pkya6TuFFXt0z72XyiU6eLKSjYz3UM8YnSUigshH/9y3WS8Ji3ah6PfvYoFwy6gK6FXV3HEQmsvn3hyy9hbUgPFtWetuA6aOZB9Hu0n+sYe0yvvCROP92b4n/+eddJ3PBm2tS0+UGvXnfSteuPXMcQn8jOhlNPhZde8i4syZ5paGzgP1/6T2LRGLcddZvrOCKBdvbZsGEDvPqq6yTpoZm24MoqyMKEYBpYr7wkiovhqKPghRcyc4lkbe1SYjEtjxTxoxEjoKICxo93nST4fv/R75mwYAIPnPIA3RPdXccRCbRDD4WOHb2xUxg1VHubijXTJq7oldeCc86BWbNg+nTXSVpXY+MG6utXa6ZNxKdOOgny8sI7MO55uBoAABLKSURBVGotk5dM5pZ3b+Hc/udy/sDzXccRCbxIxJtte/11qKpynSb1NNMmrumV14Izz/Q21GbawEjH/Yv4W14enHwyvPjipoNJZNfU1NdwwYsXUJJXwkPDHwrFshkRPxgxwmvY3njDdZLU29i0aaZNHNErrwUdO8KwYZnXtFVVfQVAdnY3x0lEpCXnnANLl8JHH7lOEkw3vXMTX674kifOeEJH/Iuk0BFHeFtMwjh2qppeBQbiHXVjeXFDTdt2jBgBU6d6yyQzRXn5y0QiuRQVHeE6ioi0YPhw71CSMA6M0u2due9w7yf3cvWQqzmxz4mu44iESlaWt1LplVe8Q0nCpHxcOYWHFBIvUdMmbqhp246zz/beZ8rAyNpGystfol27k3RjbREfa9MGTjgBxo7NzMOSdteq6lVc9PJF9Cvux13H3+U6jkgojRgB69bB22+7TpI6NQtrqPyskpIzSlxHkQympm07unWDgw/OnKZt3bqJ1NZ+S0nJWa6jiMgOjBgBCxbApEmukwTH1a9fzdLKpTx59pPkxXRhSiQdjj0WEolwjZ0qXqkAoPh0LacWd9S07cCIEfDpp/DNN66TpN+KFWMxJovi4lNdRxGRHTj9dG8pUqbeT3JXPT3tacZMHcOtR9zKgZ0PdB1HJLTica8+vfwy1NW5TpMa5ePKyd0rl7x+utgj7qhp24ERI7z3Y8e6zZFu1lrKy1+kqOhoYrG2ruOIyA60bQvHHJO595PcFR8v/Jgr/n4FB3c5mF8c/gvXcURCb8QIWLUK3nvPdZI9V7+2ntX/XE3JGSU6aVacUtO2A716wX77hf9qdlXVl1RXf62lkSIBMmIEzJkDU6a4TuJfL3z5Asf85Rja57fn6XOeJiuS5TqSSOidcALk54dj7LTyzZXYOqulkeKcmradMGIEfPwxzJ/vOkn6rFjxIgAlJWc4TiIiO+vMM70b2j7zjOsk/mOt5b8++i/Ofe5c9u+0Px9f+jFlRWWuY4lkhNxc75TbF18M/imSFeMqyCrOovCQQtdRJMOpadsJI0dCLAa/+53rJOlTXv4ihYVDyc7u7DqKiOykDh28vSMPPggrV7pO4x/1jfVc/drV/PTtn3JO/3P4x8h/UJKnU99EWtMPfgArVsCjj7pOsvsa6xupeLWC4lOLiWRpyCxu6RW4E3r0gCuugMceg6+/dp0m9Wpq5lNZ+RklJWe7jiIiu+g3v4G1a+EunWAPQGVtJWc+fSYPTnqQnx36M54+52lyY7muY4lknOOOg6OOgjvugMpK12l2z9oP11K/qp6S03XRR9xT07aTbr4ZcnLglltcJ0m98vKXALSfTSSABgyACy6A//5vWLzYdRq3lqxbwpF/OpLXZ7/Og6c8yN3H303E6M+ciAvGwJ13wrJlcP/9rtPsnvKXyzHZhrYn6IA2cU9/zXZSaSlce623d2TyZNdpUmvFihfJzx9AXl4f11FEZDfcfjs0NHizbplq+vLpDH1sKDPLZ/LKea9w5ZArXUcSyXhDh3pLuO+5J3hLuG2DpfzFctoe25asAh1gJO6padsFP/2pd8z2zTe7TpI669d/yZo1H2iWTSTAevaEUaO8JdyzZ7tO0/remfsOhz5+KHUNdXxw8QecstcpriOJSJPf/jaYS7iX/nkpNd/U0OnSTq6jiABq2nZJURH84hfw+uvw/vuu0+wZay2LFz/Mp58eSFZWWzp2vNB1JBHZA7/8pXdT21tvdZ2kdf358z9z0lMn0T3RnU9+8AmDOw12HUlENhPEJdwNVQ3Mu3UehUMLKTlL+9nEH9S07aKrr4bOnb3mLag3tK2tXc60aafz9ddXkkgczpAhU8jN7e06lojsgY4dvSXcf/sbfP656zTpt7RyKde9cR0XvXwRR5UdxYSLJ9A90d11LBFJImhLuBfdv4jaxbX0uruXbqgtvqGmbRfl5npXsj/6CF591XWaXVdR8SoTJw5k5cq36dPnfgYNel3H/IuExM9+Fr4l3FubsmwKF798MT3u68H9/7qfyw+4nNf+4zUSOQnX0USkBUFawl1bXsuC0QsoPq2YosOLXMcR2UhN22645BLo0wduugkaG12n2TkNDVXMmvVDpk49lXi8IwccMImuXX+E0clqIqFRVAQ33ACvvQYffOA6Teo02kZe+/o1jvvLcez78L48O/1ZRu0/ilnXzOLhUx8mFo25jigiOxCUJdwLfruAhsoGeo3u5TqKyBY0Yt8NsZg3xT91qrcUye8qK6fy6acH8O23D9G160844IB/U1AwwHUsEUmDa66BTp2CvYS7WXVdNY98+gj7PLgPw8cMZ0b5DEYfO5pF1y3if075H/q004m3IkERhCXc1fOqWfzAYjpd0on8/vmu44hsQU3bbvrud2G//bwrRrW1rtO0bPXqCUyefDj19WsYNOht+vT5LyKRbNexRCRN8vK8uvThh96MWxCtql7Fbe/dRvf7unP53y8nL5bHk2c9ybwfz+OGYTfQNlf3TBIJIr8v4Z538zxMlqHs9jLXUUS2oaZtN0Ui3jG2c+d6a7T9qKLiNaZMOYF4vJT99/+Edu2Ocx1JRFrBpZdC797ewCgoS7gBVlav5JZ/3kLZ/WXcPv52Dul6CO9d+B6TLpvE+YPOJx6Nu44oIntg8yXcEya4TrOldZ+uY/nfltP1uq5kd9bFbfEfNW174OSTYdgw+PWvoarKdZotLVv2FNOmnUFe3ncYPHgCOTk6VU0kU8RiXl364gt45hnXaXZsZfVKfvnPX1J2Xxl3fHAHx/c6ni+u+IJx543jyLIjdXqbSIg0L+G+8Ub/LOG21jLnhjlkFWfR/ecaL4k/qWnbA8bAnXfC0qVw/fWwZo3rRJ5Fi/6XGTMuIJEYxn77vUs83t51JBFpZd//Pgwa5M22TZ7sOk1yFVUV3PzOzZTdV8ZvP/gtJ/Y5kS+u+ILnv/s8g0oHuY4nImmw+RLue++FDRtcJ4JVb61i9TurKbuljKxElus4IkmpadtDw4bBZZfBww9Dt27eeu1Fi9xksdYyb95tzJ59DcXFZzBw4OtkZRW6CSMiTkUi3s1sy8th//3h+OPhrbf8cWW7vKqcm965ibL7y7hzwp2c1OckplwxhefOfU7NmkgGuPRSOPxw74J3r15w991uL3w31jaSOCJB5yt0CyTxLzVtKfDII/Dpp3Dqqd5Vo1694KKLYNq01s1RWTmZ+fN/TceOF7HPPs8Tjea0bgAR8ZUjj4SFC+Guu2D6dDjxRBg8GJ56Curq3OX6aOFHjJ4wmlP2OoUpV07h2XOfZWDpQHeBRKRVxWIwfjy8+Sb07+/tc3N54bvktBIGjx9MJFvDYvEvvTpTZP/9YcwY76aRV14Jzz0HAwfC8OHw3nutc3W7TZv9GTx4Av36PUYkoul9EYFEAn7+c5g3Dx5/3GvWLrjAu9fkffdBZWXrZzqt72l8dfVXPHPOMwzooNuPiGQiY+CEE+Dtt7e88N2zJ1x4oXdbJRHZJC1NmzHmJGPMTGPMbGPMjel4Dr8qK4P774cFC7x7uU2aBEcfDQcd5DVyDQ3pff5E4lDdMFtkOzK1PmVnw8UXewOhv//dq1XXXedd3b7pJm9vbmsxxtC3uG/rPaFIAGRqbYItL3z/8Ifw/PPentxTToF33/XHsm4R11I+ujfGRIEHgJOB/sB5xpj+qX4evysuhl/+Er75xtvvtmaNd2+3vn3hgQf8d9qkSCZQffL2ug0f7i1N+uQTOPZYGD0aevTw9ud+9ZXrhCKZR7XJs/WF708/hWOO8S58P/ss1Ne7TijiTjqmZA4CZltr51pra4GngTPS8DyBkJsLl18OM2bA2LHQoQNcfTV06eI1cL17e0sBunf3HuvUyft/iou9+5kUFkJ+PuTkQDwODz3k+jsSCTTVp80cfLB3RXvWLO9ggCefhO98x6tNe+3l7c/t0QO6doXOnaG0FEpKoF07b9llQYFX47KzYb/9XH83IoGm2rSZ5gvf8+fD//2fd+H7e9/zalHz2KmsbNPYqWNHaN9+09ipTZtNY6dYDD74wPV3JLLn0rHxqQuwcLPPFwEHb/0/GWNGAaMAuncP/z0xolE46yw480zvmNvHH4fqau+qdzS66W1Hnw8e7Po7EQm0HdanTKtN4O1ve/BBuO0278LQl1/uWl2KRLxBk4jsNo2dksjJgVGjvItK48bBCy9420x2pTZFo16zJxJ0zk6rsNY+AjwCcOCBB2bMamVjvNsEDBvmOomIJJOptQm8Wf5f/cp1ChFpSabWp+YL32ed5TqJiDvpWB65GOi22eddmx4TEXFN9UlE/Ei1SUS2Kx1N20RgL2NMT2NMHPg+MC4NzyMisqtUn0TEj1SbRGS7Ur480lpbb4y5GngTiAKPW2unp/p5RER2leqTiPiRapOI7Eha9rRZa18DXkvH1xYR2ROqTyLiR6pNIrI9uguziIiIiIiIj6lpExERERER8TE1bSIiIiIiIj6mpk1ERERERMTH1LSJiIiIiIj4mJo2ERERERERH1PTJiIiIiIi4mNq2kRERERERHxMTZuIiIiIiIiPqWkTERERERHxMTVtIiIiIiIiPqamTURERERExMfUtImIiIiIiPiYmjYREREREREfU9MmIiIiIiLiY2raREREREREfExNm4iIiIiIiI+paRMREREREfExNW0iIiIiIiI+pqZNRERERETEx9S0iYiIiIiI+JiaNhERERERER9T0yYiIiIiIuJjatpERERERER8TE2biIiIiIiIjxlrresMGGNWAPNT/GVLgPIUf81UU8bUUMbUSHXGHtba9in8eq1OtcnXlDE1MjWj6tO2MvW1kGpByAjByJmJGVusTb5o2tLBGDPJWnug6xzbo4ypoYypEYSMYRCEn7MypoYypkYQMoZBEH7Oypg6QcipjFvS8kgREREREREfU9MmIiIiIiLiY2Fu2h5xHWAnKGNqKGNqBCFjGATh56yMqaGMqRGEjGEQhJ+zMqZOEHIq42ZCu6dNREREREQkDMI80yYiIiIiIhJ4atpERERERER8LHRNmzHmJGPMTGPMbGPMja7zbM0Y080Y864x5ktjzHRjzI9dZ2qJMSZqjJlsjPm76yzJGGOKjDHPG2O+MsbMMMYc4jrT1owx1zX9O08zxvzNGJPjOhOAMeZxY8xyY8y0zR5rZ4x52xjzddP7ti4zhpHqU2r4vTaB6tMeZFJtckC1KXX8Xp9Um3Y7k/PaFKqmzRgTBR4ATgb6A+cZY/q7TbWNeuB6a21/YChwlQ8zNvsxMMN1iO24H3jDWrs3sC8+y2qM6QL8CDjQWjsAiALfd5tqoz8BJ2312I3AO9bavYB3mj6XFFF9Sim/1yZQfdpdf0K1qVWpNqWc3+uTatPu+ROOa1OomjbgIGC2tXautbYWeBo4w3GmLVhrl1hrP2v6eB3eL0sXt6m2ZYzpCgwH/ug6SzLGmARwBPAYgLW21lq72m2qpLKAXGNMFpAHfOs4DwDW2veBlVs9fAbw56aP/wyc2aqhwk/1KQX8XptA9WlPqDY5odqUIn6vT6pNu88PtSlsTVsXYOFmny/Ch7/UzYwxZcBg4F9ukyR1H/BzoNF1kBb0BFYATzQtQ/ijMSbfdajNWWsXA78HFgBLgDXW2rfcptquUmvtkqaPlwKlLsOEkOpTavi9NoHqU6qpNqWXalPq+L0+qTalVqvWprA1bYFhjCkAXgCutdaudZ1nc8aYU4Hl1tpPXWfZjixgf+Aha+1gYD0+WzLTtLb5DLwi2RnIN8Zc4DbVzrHevUB0P5AM5df6FJDaBKpPaaPalNn8WpsgMPVJtSlNWqM2ha1pWwx02+zzrk2P+YoxJoZXdJ6y1o51nSeJw4DTjTHf4C2TOMYY86TbSNtYBCyy1jZfaXserxD5yXHAPGvtCmttHTAWONRxpu1ZZozpBND0frnjPGGj+rTnglCbQPUp1VSb0ku1KTWCUJ9Um1KrVWtT2Jq2icBexpiexpg43sbFcY4zbcEYY/DWEs+w1v7BdZ5krLW/sNZ2tdaW4f0M/2mt9dVVDmvtUmChMaZf00PHAl86jJTMAmCoMSav6d/9WHy24Xcr44ALmz6+EHjZYZYwUn3aQ0GoTaD6lAaqTeml2pQCQahPqk0p16q1KSudX7y1WWvrjTFXA2/inTbzuLV2uuNYWzsMGAlMNcZ83vTYTdba1xxmCqprgKea/sjMBS52nGcL1tp/GWOeBz7DO/lqMvCI21QeY8zfgKOAEmPMIuBXwGjgWWPMpcB84LvuEoaP6lPGUX3aDapNrU+1KeOoNu0GP9Qm4y3BFBERERERET8K2/JIERERERGRUFHTJiIiIiIi4mNq2kRERERERHxMTZuIiIiIiIiPqWkTERERERHxMTVtIiIiIiIiPqamTURERERExMf+HxdUtCA9GZY2AAAAAElFTkSuQmCC\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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4cb5tGjvW3/JEHUISCxTaRERaQQdFrfPNNz68vfyynzCgvNwfEI0YUXuQdMAB/lIFkSAotCWmTZt8uzR9uh/qvWKFf79nT98mjR3r26idd1aIk2AotImItIIOitqurMxP1f322/4g6YMPaicG23XXrUNct27N32/dycaKivyMz8nJfpKUrCz/WPd5Zmbrbx5eXOxvVF5SAl261C45Oc3b57x589iwYQMZGRmkp6c3+pgcwfFaZWVlrFq1ipUrV+KcIycnh06dOv34mJmZiTVwVFpZWcnzzz9Pr169yMvLo3PnzuTm5pKdnY2Z8eKLL/Lxxx+z6667MmTIkB8/u/nmm5k1axY77bQTw4YNY9iwYfTu3Zvc3Fw6d+5MTk5Og98XFIU2cc7/u65pm2bMgOXL/Wfdu28d4nbZpfnth3N+jo6aGeuLivyJq4bapZrH1t5OpbLSz6C5YoXfT26ub5tyczv8fB0dlkKbiEgr6KAo8srL4aOPtg5xW7b4z4YP9wdIu+/u78dUVLT1gU/d55s2tfy7MzMbD3V138vIgFWr/AHdwoWN3zfVrPYgqeZAqe7zM8/0kx8cfvjhvPzyy03Wl5KSss1Q19hjeno6Gzdu/DGkrVy5kvU1d01vRFJSEjk5OT8JczNmzGjkZzUyMjIoLS1t8udoyvDhw38Mc4091n2el5fH4MGD2/y9dSm0SX3O+Wtza9qmt9/2gQj8xIUHHOCXjIyG26SaZf16fw1dS6SmNt0u1TwvK6ttm5Yubfy7srK2bpPqtlHDh8MFF7Tp1yVRotAmTTKzPwNDnHOnBV2LSKzQQVH0VVTAnDm1B0rvv+97tMCHory82pmfa2Z9buh5Xp6fhXrLFr99SUnDz5vz3pYt/tY/gwdvvXTu7M+gb9jge99qlsZeP/ign/Tg888/Z82aNZSXl1NWVhaVx06dOrHddtvRu3fvHx9rnicnJ7Np0yY2b97c5OOGDRuYP3/+j/99rrnmGnJycti4cSMbN27krbfe4rOaudVb6dhjj2Xjxo1s2LBhq8fGAmHPnj354Ycf2vSd9Sm0SXN8//3WIW7x4trPsrK23SbVfZ6R0bI2qLH3Skp8wKvfNvXt68NcU21SzTJypJ80UmLPttqmlPYuRoJjZv8DXAIMAzYB84DrnXPvtcN3/xmFQhGpJy0Nxozxyx//6If7LFtWe2a4tUMaY8nw4cODLiEmVFdXEwqFSG1kLFhFRQWbNm36SZgLhULtXKmIN3CgX848079etcr3yHXt6oOYSHtSaEsQZnYJcAVwHvAKUAEcBhwNRDS0mVmKc64qkvsUkcSQmgrbbx90FRINycnJ27xuLy0tjfz8fPLz89uxKpHm2267oCuQRNYBzmFKU8wsF7gOuMA5N805V+Kcq3TOPe+c+986q6aZ2X/MbJOZfWFmI+vs4wozWxj+7EszO7bOZ2eZ2ftm9g8zKwL+3IyanJlNMrNvw/v8q5kNNrMPzGyjmT1lZmnhdfPM7AUzW2tm68PP+9bZ1yAzeye8n9fN7A4ze7TO5/uE91tsZp+a2di2/D5FRERERNqTQltiGA1kAM80sd544EmgC/AccHudzxYC+wO5wF+AR82s7jmnvYFFQE/g+mbW9QtgT2Af4HLgXuA0oB8wHJgQXi8JeBAYAPQHSuvV9jjwIZCPD4yn13xgZn2AF4H/A7oClwFPm1n3ZtYoIiIiIhIohbbEkA8UNmPI4nvOuZecc9XAI8CImg+cc1OccyudcyHnXAHwLbBXnW1XOuf+7Zyrcs41d3qxvzvnNjrnvgA+B151zi1yzm0A/gvsHv7uIufc0865Lc65TfhQeCCAmfUHRgHXOOcqwtfnPVfnO04DXgr/XCHn3GvAHOCIZtYoIiIiIhIohbbEUAR0M7OmrmGsOz3XFiCjZhszO8PM5oWHGBbje8Lq3lVpWSvqWl3neWkDr3PC351lZveY2RIz2wi8A3Qxs2SgN7DOObelkVoGACfW1B2ufT9AI9NF2tkXX8A//uFnLxMRiSW33Qbvvht0FSKNU2hLDDOBcuCY1mxsZgOA+4ALgXznXBd8z1jdO6VG894RlwI7Ans75zoDB9SUBqwCuppZVp31+9V5vgx4xDnXpc6S7Zy7MYr1ikgDZs6ESy6BjRuDrkREZGuXXaZp8CW2KbQlgPBww2uAO8zsmHDPVaqZHW5mf2/GLrLxoWwtgJmdje9pay+d8D1vxWbWFbi25gPn3BL8cMc/m1mamY0Gjqqz7aPAUWb2CzNLNrMMMxtbdyITEWkfZWX+MTMz2DpEROqqqvKL2iaJZQptCcI5dwv+Hm1/woevZfies2ebse2XwC34HrvVwM+A96NW7E/9E8gECoFZwMv1Pj8VP9lKEX7CkQJ8zyLOuWX42xpcSe3P/b/o/32Rdldz72QdGIlILNEJJYkHuk9bAnHOPQY81shnf673+nvqDH90zl0FXNXItg8BDzXx3fX3b/Ve71fv9Z/qPF8JjK23y3vqfF4zsyUAZlYAfFXn89mEJy4RkeAotIlILFLbJPFAvQ0S98xsVPgeb0lmVnPD8CZ7EEWkfZWW+ptnb+P+yiIi7U6hTeKBetqkI+gFTMPf2mA5cL5z7pNgSxKR+kpLdVAkIrFHoU3igUKbxD3n3PPA80HXISLbptAmIrFIoU3iQVSGR5rZYWb2tZl9Z2ZXROM7REQkvii0iUgsqgltGRnB1iGyLREPbeEbHt8BHA7sDEwws50j/T0iIhJfFNpEJBapp03iQTSGR+4FfOecWwRgZk/iJ4b4srENunVNdgP7pUahFBEJyvfLKilcV21NrymJQqFNRGKRQpvEg2iEtj74e2HVWA7sXX8lMzsXOBegf58UPnylXxRKEZGg7PWLZU2vJAlFoU1EYpFCm8SDwKb8d87d65wb6Zwb2T1f8z+LiHR0Cm0iEosU2iQeRCO0rQDqdpv1Db8nIiIJrKxMB0UiEnvKyvyj2ieJZdEIbR8BQ81skJmlAacAz0Xhe0REJI6op01EYpF62iQeRPyaNudclZldCLwCJAMPOOe+iPT3iIhIfCkt1ZTaIhJ7FNokHkTl5trOuZeAl6KxbxERiU/qaRORWKT7tEk8CGwiEhERSSwKbSISi0pLIS0NknRULDFM/3uKiEjUVVbCpk3QtWvQlYiIbG39erVNEvsU2kREJOrWrfOP+fnB1iEiUl9hodomiX0KbSIiEnWFhf6xW7dg6xARqa+wUG2TxD6FNhERiTqFNhGJVQptEg8U2kREJOoU2kQkVim0STxQaBMRkahTaBORWBQKQVGR2iaJfQptIiISdTWhTRf7i0gsKS72wU2hTWKdQpuIiERdYSF06gTp6UFXIiJSS6MAJF4otImISNTpmhERiUUKbRIvFNpERCTqFNpEJBYptEm8UGgTEZGoU2gTkVik0CbxQqFNRESiTqFNRGKRQpvEC4U2ERGJOoU2EYlFhYV+gqTs7KArEdk2hTYREYmqsjLYvFmhTURiT80JJbOgKxHZNoU2ERGJqqIi/6jQJiKxRqMAJF4otImISFTpmhERiVVFRWqbJD4otImISFQptIlIrFJPm8QLhTYREYkqhTYRiVUKbRIvFNpERCSqFNpEJBZVVcH69WqbJD4otIlIQjGzi83sCzP73MyeMLOMoGvq6GpCW9euwdYhEsvUNrW/9evBOYU2iQ8KbSKSMMysD/A7YKRzbjiQDJwSbFUdX2Eh5OVBSkrQlYjEJrVNwdAoAIknCm0ikmhSgEwzSwGygJUB19Ph6ZoRkWZR29TOFNoknii0iUjCcM6tAG4GlgKrgA3OuVfrrmNm55rZHDObs3bt2iDK7HAU2kS2rTltE6h9ijSFNoknCm0ikjDMLA84GhgE9Aayzey0uus45+51zo10zo3s3r17EGV2OAptItvWnLYJ1D5FmkKbxBOFNhFJJD8HFjvn1jrnKoFpwJiAa+rwioogPz/oKkRimtqmANSENrVPEg8U2kQkkSwF9jGzLDMzYBywIOCaOjz1tIk0SW1TAAoLISsLMjODrkSkaQptIpIwnHOzganAx8Bn+Dbw3kCL6uC2bIHSUoU2kW1R2xQMnVCSeKIJmEUkoTjnrgWuDbqORKFrRkSaR21T+1Nok3iinjYREYkahTYRiVUKbRJPFNpERCRqFNpEJFYptEk8UWgTEZGoUWgTkVil0CbxRKFNRESiRqFNRGJRRQVs3Ki2SeKHQpuIiERNYSEkJUGXLkFXIiJSq6jIPyq0SbxQaBMRkagpLISuXSE5OehKRERqaRSAxBuFNhERiRpdMyIisUihTeKNQpuIiESNQpuIxCINj5R40+rQZmb9zOwtM/vSzL4ws4vC73c1s9fM7NvwY17kyhURkXii0CYisUg9bRJv2tLTVgVc6pzbGdgHuMDMdgauAN5wzg0F3gi/FhGRBKTQJiKxqCa05ecHW4dIc7U6tDnnVjnnPg4/3wQsAPoARwMPh1d7GDimrUWKiEj8cU6hTURiU2EhdO4MaWlBVyLSPBG5ps3MBgK7A7OBns65VeGPfgB6RuI7REQkvmzaBJWVCm3N5RyUlARdhUhi0AmlltmyxbdREpw2hzYzywGeBn7vnNtY9zPnnAMa/E9sZuea2Rwzm7O2qLqtZYiISIzRNSNNKyqCp56Cc86BAQMgJwf+8Aeo1p9FkahSaNu2qir44AP4y19g3319r+SIEbBoUdCVJa6UtmxsZqn4wPaYc25a+O3VZradc26VmW0HrGloW+fcvcC9ACNHZCi7i4h0MO0Z2pYvhwsugO+/h7w8fzPvvLyGl/qfpadHv74aFRX+QOi11+DVV2HuXH/2OjcXxo2D/feHv/8dPv0UnnjC1ycikVdYCD3bYSxYKAS33AL/+Y8/KbOt9qn++506gVn0a6yxcKFvl159Fd58EzZu9N8/ahRcdBE8+CCMHAkFBXDIIe1Xl3itDm1mZsD9wALn3K11PnoOOBO4Mfw4vU0ViohIXGqv0PbsszBxIpSXw8EHQ3GxPxu8fr1fmhpymJnZ8AFTly7+7HKnTn6ped7QY1ZWwwdXzsFXX9UeCL39tq8nORlGj4Y//xkOPdQfCKWE/yKPHesD6KhRMH067LJLpH9jIlJYGP1/W6tWwRlnwOuv+96qzExYswa++ca3TcXFPtQ1Jjm5tl2q3z5tqz2q+9ipU23bUl9xsQ9nNe3T4sX+/QED4OSTfTAbNw66dvXvT5oExxwDhx3mTy5dckn7hspE15aetn2B04HPzGxe+L0r8WHtKTObCCwBTmpbiSIiEo+iHdpKS+HSS+Guu2CPPXzP1A47/HS9igp/cFIT4moOluq+rrssXw6ffebX2bRp2wdVNZKSfhruOnXygW35cr/O0KFw1ln+QOigg/x6Dfn1r/3B5PHHwz77+DP0xx7b6l+TiDQg2sMjX3oJzjzTn6S5914/BLp+wAmFfBvT3LapuBiWLPHPN270J6qaIzPzp2Fuyxbf0x8K+R7Agw/27emhh8KQIQ2HscGDYeZM345ddhl88gncd5/fv0Rfq0Obc+49oLF8Pa61+xURkY4hmqHt889hwgT/eOmlcP31jQ9zTEuDHj380lLO+YObTZv8snFjw4+NfbbPPv4g6JBDYODA5n/vmDEwZw4cd5xfrrkGrr3Wh0MRaZvSUh+motE2lZfDFVfAP/8JP/sZPPkk7Lxzw+smJfmh0bm5LWsfalRU1LY/LW2fMjPhqqt8+7T33pCa2rzvzMmBKVPghhvg6qthwQJ45hno37/l9UvLtOmaNhERkcYUFvphOY31KLWGc3DPPXDxxX6///2vH6oTLWaQne2XXr2i9z0N6dPHD6ecNAmuuw7mzYNHHons71MkERUV+cdIh7avv4ZTTvH/Vi+8EP7f/4OMjMh+R11paf4+c+19rzkzH/hGjIBTT/XDu6dMgQMPbN86Eo3O2YmISFTUDD+K1DUP69b5IYPnnw8HHOAn64hmYIsFGRlw//3w73/Diy/6M+LffBN0VSLxLdKjAJzzk3TssQcsW+avRf33v6Mb2GLBL38JH37or3n7+c/hjjt0W4BoUmgTEZGoiOQ1I++848/qPv+8P3v93/+2f89XUMz8WfvXX/e/01GjfG5knP8AACAASURBVIATkdaJZGjbsAH+53/gV7+CvfbyJ5PGj2/7fuPFjjvC7Nn+BNqFF/pr95p7rZ20jEKbiIhERWFh24ftVFX5GRYPOshfs/bBB/4C+ES8tmvsWH+d2+DBcNRR/poSndUWabma0NbW9mnWLNhtNz808Prr/YmVPn3aXl+8yc31vYt/+hM88IAfJrlyZdBVdTwJ+GdPRETaQ1t72pYu9WHtL3+B007zM5WNGhW5+uLRgAHw3nv+upmrroKTToLNm4OuSiS+tLWnrboa/vY32G8///rdd+HKK/0U/YkqKQn++leYOtVPELXnnn6mSYkchTYREYmKtoS2p5/2wyFrJt94+GE/TbX4e8I99hjcfDNMm+YnZhGR5qsJbTX3H2uJlSv9jItXXgknnODbqNGjI1tfPDv+eN8DmZXlbw1QVRV0RR2HZo8UEZGIqqiAyko/Q1tLQ9uWLX5myHvv9b1qjz/u7xkkWzPztzrYbz8/c5uINM05P+V9YaG/QXVjN51uzAsv+CBSWuonCDr7bN1cuiHDh8NHH8Hq1S3/HUvj1NMmIiIRtdde/l4+oZA/yFm7tnnbffaZD2r33guXX+6HASqwbdveeyf2kCyRlpgyBbp08bMcrl8PH3/cvOtCy8rgoov8taT9+vntfvUrBbZt6doVdtop6Co6FoU2ERGJqKuvrn3+6ad+lsf99/ezPn799U/Xd84fRI0a5XvnXnkFbrrJ34NIRCRSjjxy62n499zT3xT6ggt8u9PQrIcLFsA++8C//gW//70f+rfjju1Xs0gNhTYREYmo44/3QWz5cj/b4dVX+8kyLr8chg3zBzw1PWlr1sCxx/qpog86CObP99eLiIhEWna2H9q4YQMsXOjvrTZqFDz0kJ+yvls3OPFEfx1tUZEfAjlyJKxY4UcN/OMffhZbkSBopKmIiERFnz5+2XNPP23/0qX+PmvTp8M//+l73sz8NQ+33uqHHyXiVP4i0r46d/bL9tvXXqP25pvw3HN+mTrVt03OwbhxPsRtt13QVUuiU2iLAwsqtnDH2oP4oaxlU6f1ztzARd3fYnBqTpQqExFpvpphSBdc4M90v/KKH2p02mmwxx5BVyciiSoz0w+dPPJIuOsuP0LghRd8UPvNb3QySWKDQlsceGj9GD69YTc6fb2+RdvN+dkQpv6pmD/kfxulykREWic3199j7KSTgq5ERKRWUpKfTGmvvYKuRGRrCm1xoLgyk+zvN1P95Tct2q5z9s94f91g3sluWWjLsEp2TK0iNymzRduJiIiIiEjkKbR1YEmLVlB86xAuyzu/RduVdjcmnP4GV3ZrYJo3EREREZHWKC31dyO/5ho47rigq4krCm0dWHXROjKnf0hL+8u67TSUOUf1pzp/wTbXSzYN8hYRERGRZnrjDX8vmOzsoCuJOwpt8lPrNvDtC0MZsv2gxtcxx8EjFnB3v7dJNd3ZVURERESaMH06dOoEY8cGXUncUWiTn6hevYY+/yjGkrfRk5aczDvX7Er5qa8rtImIxLD58+cze/ZszjjjDNJ1kykRCUoo5O/7cvjhuuFdKyi0SYNcZQWuchsrmJGz1Dhv6WFkp5Q3ub/0pCpO7jqbfTM0pFJEpD298sorXH755UyYMEGhTUSCM3s2rF4NRx8ddCVxSaFNWsc5ej+9kKL3e1No1uTqVbnp/OGKfry367R2KE5ERGqUlpYCkJmpGYFFJEDTp0NKChxxRNCVxCWFNmm1qh9Www+rm7VuWn5XFq0eyLzypnvlZNu6JVfSN0U3TBeR5iktLSU1NZXkZA1lF5EATZ8OBx4IXboEXUlcUmiTdhHaXMKAx5M4e/bFQZcS97YcuJlZY+4mLzkr6FJEJA6Ulpaql01EgvXNN/DVVzBpUtCVxC2FNmkXrryctFfm0CPoQjqAFZ3HUDI6RF7QhYhIXFBoE5HATZ/uH8ePD7aOOKbQFgcOyP2Ga84cQfoRY1q0Xfp66P3iMqqWLItSZSIiEusU2kQkcNOnw267wYABQVcStxTa4sBJOWv4xfG3EGrhdv8sHM3sr0aRotAmIpKwFNpEJFCrV8MHH8A11wRdSVxTaIsDqZZMt+SW3zl+l6wVvLjrfuQn7dms9dMLS3ELFuI0WYiISIeh0CYigXrhBXBOU/23kUJbB3ZE1jKqz3uK1VW5zVr/zo/GsvOf8qlasTLKlYmISHspLS0lIyMj6DJEJFFNnw79+/vhkdJqCm0dWF5yFmd0LgQKm7X+WwN3JNS9C8llZc1a35WWEdqypQ0ViohItJWWlpKVpdlmRSQAJSXw2mtwzjnQjPv6SuMU2uRH5/WdwZ+vO4otZX2aXNc5o9Pr2XR78CNcVVU7VCciIq1RWlpKfn5+0GWISCJ67TUoK9PQyAhQaJMfjc/ewviRBc1at9qFGLL+PLr9JxkU2kREYpauaRORwEyfDrm5/qba0iYKbSIxLKVfX1Yf2o+KLnWGFOy1gWxLCq4oEYkrCm0iEojqaj8JyZFHQmpq0NXEPYU2kRhWumNPDr3wfX7d9YMf3+uUZOS1YjZREUlMZWVlCm0i0v4++AAKCzU0MkIU2qR9JCWTPHgAVd07BV1JXFk/LJ3dspcwKDUn6FJEJE6pp01EAjF9uu9hO+ywoCvpEBTapF0kd87hm/N6cPzBs4IuJa70Ty/i4MyVgHrWRKR1FNpEpN0550PbwQdD585BV9MhKLRJ+0hJIW3AZm7qOS/oSuKQApuItE5VVRVVVVUKbSLSvhYsgO++g0suCbqSDkOzGYiIiHRQpaWlAAptItK+pk/3j+PHB1tHB6LQJiIJxcy6mNlUM/vKzBaY2eigaxKJFoW2+KG2STqU6dNh5Ejo0/S9f6V5FNpEJNHcBrzsnBsGjAAWBFyPSNQotMUVtU3SMaxaBbNna9bICGtzaDOzZDP7xMxeCL8eZGazzew7Mysws7S2lyki0nZmlgscANwP4JyrcM4VB1uVSPQotMUHtU3SoTz/vH9UaIuoSPS0XcTWZ4NuAv7hnBsCrAcmRuA7JEaUu0reKE3moY29SStKbnL9pKwskncaSsXwAXTN2dIOFYps0yBgLfBg+GTTZDPbaqYXMzvXzOaY2Zy1a9cGU6VIhCi0xY0m2yZQ+yRxYvp0GDQIhg8PupIOpU2hzcz6AkcCk8OvDTgYmBpe5WHgmLZ8h8SWBRUhzn/qXP7zv+MZ/Pg6XEXFNtcPDR/M0uvT2Pnmz7hph6nbXFekHaQAewB3Oed2B0qAK+qu4Jy71zk30jk3snv37kHUKBIxCm1xo8m2CdQ+SRzYvBneeMP3spkFXU2H0tYp//8JXA7U3DE5Hyh2zlWFXy8HdAViB1IcyiRvAWS88CHVzVi/sks6v9rhTS7pughdQikxYDmw3Dk3O/x6Kg0cGIl0FAptcUNtk3QMr7wC5eUaGhkFrT6KNrNfAmucc3NbuX1tF39Rcw7/RUTaxjn3A7DMzHYMvzUO+DLAkkSiSqEtPqhtkg5j+nTo2hX22y/oSjqctvS07QuMN7MjgAygM37moy5mlhLubesLrGhoY+fcvcC9ACNHZLg21CEi0hK/BR4LT5K0CDg74HpEokahLa6obZL4VlUFL74IRx4JKW0dzCf1tfo36pz7I/BHADMbC1zmnDvVzKYAJwBPAmcC0yNQp4hIRDjn5gEjg65DpD0otMUPtU0S9957D9at09DIKInGRUZ/AC4xs+/w17jdH4XvEBERkSYotIlIu5k2DdLT4Re/CLqSDikifZfOuRnAjPDzRcBekdiviIiItJ5Cm4i0i8pKePJJOOooyMkJupoOSdP5iYiIdFAKbSLSLl55BdauhdNPD7qSDkuhTUREpIOqCW3p6ekBVyIiHdqjj0J+Phx2WNCVdFgKbSIiIh1UWVkZGRkZmG5yKyLRsmGDn+r/5JMhLS3oajoshTYREZEOqrS0VEMjRSS6nn4ayso0NDLKFNpEREQ6KIU2EYm6Rx6BoUNh772DrqRDU2gTERHpoBTaRCSqli6FGTPgtNNAw7CjSqFNRESkg1JoE5Goevxx/3jqqcHWkQAU2kREREREpGWc80Mjx4yBwYODrqbDi8jNtUVaqtqFgi6h1ZJN5zpEJD6kp6dTXl4edBki0hF98gl8+SXcdVfQlSQEhTZpdzcVDeXuDw+EyvgLPzvusIJHhz5Ft+TsoEsREWmSQpuIRM0jj0BqKpx0UtCVJASFNml3D321Dzv/aTnV69YHXUqLrZq0J2svMrolB12JiEjTFNpEJCqqquCJJ+DII6Fr16CrSQgKbRJVqcXl3P/1aL7o0/vH96q/zSG0+XtcHB5I5KwIcfGiE9kjbxkTu37A4NScoEsSEWmUQpuIRMXrr8Pq1bo3WztSaJOoSvp8IQP+1IeV6f1/fG/o+uVUbd4cYFWtl/vGN7gvezBjlzGkX1nFtd2/DLokEZFGKbSJSFQ88gjk5fmeNmkXCm0SVaEtW2DBt1u/F1AtkVBdtA6K1pGbsjMfrR/AvM6f0DelSte4iUhMUmgTkYgrKYFnn/X3ZktPD7qahBF/M0GIxABb9gPFt/fnrFsv5ozvTgy6HBGRBmVkZBAKhaiqqgq6FBHpKF54AbZsgQkTgq4koainTaQVqovWkT11Np2ysliw6y5U7xDSrQBEJOakh8+Cl5WVkZOja3BFJAIKCqBXL9h//6ArSSgKbdIsz5VkccWnx1G2Kpsh320JupyY4Sqr6DYzhaGpv2bYgFU8NGQKPTRUUkRiRE1oKy8vV2gTkbbbuBFeegnOPReSNZV2e1Jok2Z5fM0+9P+bw776nFBpWdDlxAxXWUH+Yx/TbUoaP5w2nO8vT6OH2jARiRF1Q5uISJs99xyUl8PJJwddScJRaJNmqahOJmlLBdUlJUGXEnNceTmuvJzkcgg5DZEUkdih0CYiEVVQAH37wujRQVeScHSEKSIi0kEptIlIxKxfD6+8AiedBEmKEO1NPW0SnKRkkjvnQEqM/m9YVUX1xs0Qqm7W6klVsLCyB71TltAzOZ10S41ygSIi26bQJiIR8+yzUFmpoZEBidGjZUkEyUMG8s1vupM2IDZvtF22Iodh96yj+stvmrV+/pwibvnnSVzXF3537Atc0GVZlCsUEdk2hTYRiZiCAhg0CEaNCrqShKTQJoGp6t6JU8a9z//1+CzoUhp0U9FQXnt2f5K/bN761V9+Q/cvoefwYbw/dohCm4gETqFNRCKisBBefx0uuwzMgq4mISm0Sbuw9HS2HDaC9UNr/5fb0jvEpOzFAVa1bSMyl3LPMWl0GjGG7d7fhPsoNsOliEhjFNpEJCKmTYPqag2NDJBCm7SLpJxsVp5UyZv73/rje6lAt+RMIDbnyB+XuYX3j72ZRVVZnJdyIb0/CroiEZGWUWgTkYh46ikYOhR22y3oShKWQptERUqf3lT27w5Jvgt9S+dU+vVYQ/+U+Lm5a6ols11KDrCZkOYUEZE4pNAmIm22ejW89RZceaWGRgZIoU2iYtVRA9hn4id0TfX3dctIquSXnT4F0oMtTEQkgSi0iUibPf00hEJ+qn8JjEKbtF1SMkmZGVhy7TDHkj5wXa836JacXWdFBTYRkfak0CYibVZQADvtBMOHB11JQlNokzZL2nVHvjmzM3QLHxQY/HyHeXRKSgu2MBGRBKfQJiJtsnIlvPsuXHuthkYGTKFN2qxkQA7XHj6VMzoX1vtEF4KJiARJoU1E2mTKFHBOs0bGAIU2aZGk7GxKDtmFTX1q/9fZsEOIwWlrgKTgChMRkZ9QaBORNikogF13hWHDgq4k4Sm0SYskdc9n09kbeXjEQz++18mq6JuSGVxRIiLSoJrQVlZWFnAlIhJ3li6FmTPh+uuDrkRQaJNm6pW5ic+GbU9SpWOX7t+wa1pG0CWJiEgTUlJSMDP1tIlIyz31lH/U0MiYoNAmzfLb7m/yyDVbqCaJU/NmAQptIiKxzsxIT09XaBORlnvqKdhzTxg8OOhKBIU2aaad0rK4oef88CsFNhGReJGRkaHQJiIts2gRfPQR/P3vQVciYZo5QkREpANTT5uItFjN0EjdUDtmKLSJiIh0YAptItJiBQWwzz4wYEDQlUiYQpuIiEgHptAmIi3yzTcwb54mIIkxbQptZtbFzKaa2VdmtsDMRptZVzN7zcy+DT/mRapYERERaRmFNhFpkYIC/3jCCcHWIVtpa0/bbcDLzrlhwAhgAXAF8IZzbijwRvi1iIiItLOysjKWL19Obm5u0KWISLwoKID99oO+fYOuROpodWgzs1zgAOB+AOdchXOuGDgaeDi82sPAMW0tUkRERFpu2rRpFBcXc/rppwddiojEgy++8IuGRsactvS0DQLWAg+a2SdmNtnMsoGezrlV4XV+AHo2tLGZnWtmc8xsztqi6jaUISIiIg2ZPHkygwYNYuzYsUGXIiLxoKAAkpI0NDIGtSW0pQB7AHc553YHSqg3FNI55wDX0MbOuXudcyOdcyO75ye3oQwRERGp77vvvuOtt95i4sSJJCVp3jERaYJzfqr/Aw+EXr2CrkbqaUsrvhxY7pybHX49FR/iVpvZdgDhxzVtK1FERERa6oEHHiApKYmzzjor6FJEJB7Mnw9ff62hkTGq1aHNOfcDsMzMdgy/NQ74EngOODP83pnA9DZVKCIiIi1SVVXFQw89xBFHHEGfPn2CLkdE4kFBASQnw/HHB12JNCCljdv/FnjMzNKARcDZ+CD4lJlNBJYAupW6iIhIO/rvf//LqlWrOOecc4IuRUTigXM+tI0bB926BV2NNKBNoc05Nw8Y2cBH49qyXxEREWm9yZMn06tXL4444oigSxGReDB3LixaBFddFXQl0ghdmSwiItKBrFy5khdffJGzzjqL1NTUoMsRkXhQUACpqXDssUFXIo1QaBMREelAHn74Yaqrq/nVr34VdCkiEg9qZo089FDIywu6GmmEQpuIiEgHEQqFuP/++xk7dixDhw4NuhwRiQezZsHSpZo1MsYptIlIwjGzZDP7xMxeCLoWkUh6++23WbhwoSYgiVNqmyQQBQWQlgbjxwddiWyDQpuIJKKLgAVBFyESaZMnT6ZLly4cd9xxQZciraO2SdpXKARTpsDhh0NubtDVyDYotIlIQjGzvsCRwOSgaxGJpHXr1vH0009z6qmnkpmZGXQ50kJqmyQQ778PK1dqaGQcUGgTkUTzT+ByIBR0ISKR9Nhjj1FeXq6hkfFLbZO0v4ICyMyEo44KuhJpgkKbiCQMM/slsMY5N3cb65xrZnPMbM7atWvbsTqR1nPOcd9997Hnnnuy2267BV2OtFBz2qbwemqfJHKqq2HqVDjySMjJCboaaYJCm4gkkn2B8Wb2PfAkcLCZPVp3Befcvc65kc65kd27dw+iRpEWmzNnDp999pl62eJXk20TqH2SCHv7bVi9WkMj44RCm4gkDOfcH51zfZ1zA4FTgDedc6cFXJZIm02ePJnMzEwmTJgQdCnSCmqbJBAFBZCdDUccEXQl0gwKbSIiInGspKSEJ554gpNOOolczf4mIs1RWQlPP+2n+c/KCroaaYaUoAsQEQmCc24GMCPgMkTabMqUKWzatElDIzsItU3SLiZPhqIiDY2MI+ppExERiWOTJ09mxx13ZN999w26FBGJdc7BjTfCpEkwbpyGRsYRhTYREZE4tWDBAt5//33OOecczCzockQkllVXw29/C3/8I0yYAC+9BKmpQVclzaTQJiIiEqfuv/9+UlJSOOOMM4IuRURiWVmZHwp5xx1w6aXw6KOQlhZ0VdICuqZNREQkDlVUVPDwww9z9NFH06NHj6DLEZFYtX49HH00vPsu3HorXHxx0BVJKyi0iYiIxKHnnnuOwsJCJk6cGHQpIhKrli2Dww6D776DJ56AU04JuiJpJYU2ERGRODR58mT69u3LoYceGnQpIhKLPv/cB7ZNm+Dll+Ggg4KuSNpAoU2kEYXVJUzfPJjPtvQls9AFXY6IyI+WLFnCq6++ytVXX01ycnLQ5YhIrHn7bT8kMisL3nkHRowIuiJpI4U2kUa8UDKI2+84jm6fldJz4VKqgi5IRCTswQcfBODss88OuBIRiTlTpsBpp8H22/setgEDgq5IIkCzR4rUsyVUwaqqzXxW0pdun5WS9PYnVC1f0eR2lpJCcufOhHLSSE9WxBOR6KiuruaBBx7gkEMOYeDAgUGXIyKx5N//9rNEjhwJ77+vwNaBqKdNpJ6LVx7IOy/uTtYqR68W9LBV7/szvp6QSudem7i026yo1igiiev1119n2bJl3HLLLUGXIiKxZMYM+N3v4Jhj4PHHITMz6IokghTaROp5a+EODPnXAqrXr2/RkMjiwRk8cejt7JOh60tEJHruueceunXrxvjx44MuRURiye23Q9eufpbIjIygq5EI0/BIERGROFFQUMAzzzzD+eefT3p6etDliEisWLECnn0WJk5UYOugFNpERETiwNdff80555zD6NGjufrqq4MuR0RiyX33QSgEv/lN0JVIlGh4pAhQ6aqZWZ7MV+W9qVqTCdXVzdvQjJT+fanunktJbyMrqRLQ8EgRiaySkhKOP/54MjIyKCgoIDU1NeiSRCRWVFb60HbYYTB4cNDVSJQotIkAq6tLOeuFS+n/cogdV2ygenNJs7aztDQWn9GPg8fP5bicZWyvf1EiEmHOOSZNmsSXX37Jyy+/TL9+/YIuSURiyXPPwcqVcM89QVciUaRDTBFgizM6LUom/aXZhJqzgRmWlkZSpxxKty/n9j6zwx9oHLmIRNb999/Pf/7zH6699loOPfTQoMsRkVhz551+av/DDw+6EokihTaRVkjp35fFZ/SjdPtyzthD0/uLSHR88sknXHjhhRxyyCG6jk1EfmrBAnjzTbjhBkjW5RkdmUKbSCtUd8/l4PFz6/SwiYhEVnFxMSeeeCLdunXjscceI1kHZCJS3913Q2qqnzVSOjSFNkloX1SU8pflv+Srwh7kLmnm5CMiIlHmnOPss89myZIlzJgxg+7duwddkojEmpISeOghOPFE6NEj6GokyhTaJKE9tWEkq28aTL95KwmtW9q869lERKLstttu49lnn+WWW25h3333DbocEYlFjz8OGzfCpElBVyLtQKFNEtLCys3MK+/NWz/sQNbyEqqWLQ+6JBERAObOncvll1/O+PHjufjii4MuR0RikXN+ApJdd4UxY4KuRtqBQpskpDMXnEH1wz3IWl1J0uLv0MBIEYkFGzdu5OSTT6Znz5488MADmFnQJYlILJo9G+bN89e0qZ1ICAptklDKXSWVrpoVy7sy7LnPCJWUtCywmWEpqYRSk0kyDaYUkchxznH++eezePFiZsyYQX5+ftAliUisuvNO6NQJTj016EqknSi0ScJYVbWZ8fN/RfEX+fSe63AVlS3eR2i/3fj+qAxcnzIu6TI/ClWKSKJ6+OGHefzxx7nuuuvYf//9gy5HRGJVYSEUFMCvfw05OUFXI+1EoU0SxsrqNKpfzGf7ez4EF8I51+J9FI7IZMqJ/2CXtBRSTdNvi0hkLFiwgAsuuICDDjqIK6+8MuhyRCSWPfAAVFTA+ecHXYm0I4U26fDmV5Txjx8OYf7a7ei0vBpCLbuCzVJSCI3ahU2DMin+WSVdkytJtfQoVSsiiaa0tJRTTjmFrKwsHn30Ud2PTUQaV13tr2M78EDYZZegq5F21KbQZmYXA+cADvgMOBvYDngSyAfmAqc75yraWKdIqz1QtB+L/zqMXgvWElq7oMXT+ltmJt+dlsGdv3iQfinF9EnOikqdIpKYLrvsMubPn8+LL75I7969gy5HRGLZK6/A4sVw441BVyLtLKm1G5pZH+B3wEjn3HAgGTgFuAn4h3NuCLAe0C3aJRBLqzbzRmkyH63tT9biDVQt+p7Qpk3N3t5S00jp1xcG9yO79yYOyypnl7RMkq3V/2xERLYybdo07rzzTi699FKOOOKIoMsRkVh3553Qqxccc0zQlUg7a+vwyBQg08wqgSxgFXAw8D/hzx8G/gzc1cbvEWmRahfipM/PIlTQnezVVbD86xbvw3bcni8vzWbE9su5vve7UahSRBLZkiVLmDhxIiNHjuSGG24IuhwRiXXffw8vvQR/+hOkpQVdjbSzVoc259wKM7sZWAqUAq/ih0MWO+eqwqstB/o0tL2ZnQucC9C/jy6tk8ipdiHKXRVrFuezw5Mf48rLW34ftqRkqvIzOWOPWfyl+xfRKFNEElhlZSUTJkygurqaJ598kjQdgIlIU+65B5KS4Nxzg65EAtDqtGRmecDRwCCgGJgCHNbc7Z1z9wL3AowckdHyafxEGrC0ajMnfX4Waxbl0+s9w1VWNb1RPaEDd2fpzzOo7FfBFTlfRaFKEUl01157LTNnzuSJJ55g8ODBQZcjIrGuvBwmT4ajjoK+fYOuRgLQli6unwOLnXNrAcxsGrAv0MXMUsK9bX2BFW0vU6R5FlV2JvRUd3Z44mMf2Fo4UyTAD6MymXb6LQxKSSYrSWe/RSSyXnvtNW688UbOOeccTjnllKDLEZF4MHWqvz/bpElBVyIBaUtoWwrsY2ZZ+OGR44A5wFvACfgZJM8Epre1SJGmzK8oY3Lh/ny0tj/ZP1ThystbtL2lpMDuO1HSN4vNO1TSPTlEVlJmlKoVkUS1evVqTj/9dIYNG8Ztt90WdDkiEi/uvBOGDoVx44KuRALSlmvaZpvZVOBjoAr4BD/c8UXgSTP7v/B790eiUJFtue2Hn7PwrzuRt6gYVnzd4mvYknI7s+CcDP429imGpq0mX4FNRCIsFApxxhlnsGHDBl577TWysnT7EBFphnnz4IMP4NZb/TVtkpDaNAOIc+5a4Np6by8C9mrLfkWaa1XVZpZVpzO/sDfdvy6k+rvFLdreUtNIzs8j1LMr3fps4JRO6wENiRSRyLv55pt5CBkBlQAAIABJREFU9dVXufvuu/nZz34WdDkiEi/uugsyM+Gss4KuRAKkaRslblW6ao7+7Gyqn+tGzspq3OoFLd/J8KF8eUEmAwes5aqBb0S+SBERYNasWVx11VWccMIJnKuZ30SkuTZsgEcfhQkTIC8v6GokQAptErcqXTXrvspnyP0f4aqqCLViH+U9s7ho9Gv8Pu/7SJcnIgJAcXExEyZMoG/fvtx3332YWdAlicj/Z+/O46Mqz/6Pf6/sCxC2gAgoqIjgCiLuy1N9rFur1QqodW0f7M/aVlvbqhUV3J9q1bpV2rorahFbbX1arUttq6IsKgRQQEV2SSAQkpBl5v79cc+QAAkkYTLnzMzn/XrNa2bOzJy5GPHi/p5zn3NSxZNPSjU1nIAEhDaknsUNG3Xh/Au0fGkv9XtfcpH2nyEyeuwILT+6ULWD6zWy8IvEFwkAkpxz+t73vqdly5bpX//6l7p37x50SQBShXP+BCSHHCIdfHDQ1SBghDaknDn1uyjyRB/t86eP5err5Vz7L/O3/KhCvfC9O7VrjqmL5UviwF4AiTd58mS98MILuuOOO3TYYYcFXQ6AVPLPf0rz50uPPhp0JQgBQhtCLeKiermmm97asM/mZbPKB6podYOiNTXtWpfl5kn7DdGmXYpUu0e9ds0xlXCWSACdZM6cObriiit04okn6qqrrgq6HACp5sEH/XFsY8cGXQlCgNCGUKt19bry9XO192ObZBG/R624vlH2+cJ2n9Y/u1cPzftBoX5xxCvav2BpbA8bACRedXW1xo4dq5KSEj3xxBPK4jTdANpjxQrpxRelH//YnzkSGY/QhlBqcBGtjNRqRWOhCpflSNPnbJ4G2d7JkJaTo6ySbor27amBAyv0/e7LxXRIAJ3piiuu0IIFC/Tqq6+qb9++QZcDINXcdZcUiUjf/37QlSAkCG0IpXfrsnXRX36qkk+zNXDGRn8wbkeNGKb53ytQ6YBKXbvHa4krEgBa8Oyzz+r3v/+9rrnmGp1wwglBlwMg1cyfL/3mN9J3vyvttVfQ1SAkCG0IpYV1u2i3v0eV/9fpO72umv6Fuvm4F3Re14oEVAYArVu8eLHGjx+vI444QhMnTgy6HACpxjk/JbK4WLr11qCrQYgQ2hC4mmi9rlxxrN5YNHTz1Ef3VYH2Xra+Q9dei4seO0KrRhdq494NGpK3SlJuAqoFgJbV19dr3Lhxys7O1jPPPKPcXHoOgHb605+k116T7r1XKi0NuhqECKENgdvoGvT2KyM05J6yzctcJKpodfvODrkFMy09vkAvXnCnSrOdenCWSACd7Nprr9WMGTP0wgsvaPfddw+6HACpprZW+slPpP3242La2AahDUn3YV2d/r5xP22K+q3QFQ3FKlrhFKlcv9Prtvx82dDBauhVpPrd6rV7To6KsvJ2er0AsD2vvPKK7rrrLl122WU688wzgy4HQCr61a+kL76Q3nxTymGIji3xNwJJd8XCsdK9pcqp9iftt4jTLp9/qcYErDu7T6nmXVms7x78H11TvFD5xl9xAJ1rxYoVuvDCC3XAAQforrvuCrocAKloyRLpttukMWOk444LuhqEECNaJM26SI2qXVRfruqpfd5ZpMi6dZtf62hgs/x8ZRUWbH4e7dVN+++xXNf1XhBbwqn9AXSeSCSi73znO6qpqdFzzz2ngoKCHX8IALZ21VWSmd/bBrSA0IakKI9U69j3x8s+KNGA+Y2K1uzE8WpxWdlaN3akKr6+STJ/CpOiojrdvOvbO79uAGiDW2+9VW+++aYeffRR7bPPPkGXAyAVvf66NHWqdNNN0m67BV0NQorQhqRYH3XK+XeJdrn7HUntv0B2Syw7W+UjneYdN1n5xlnaACTXv/71L914440677zzdOGFFwZdDoBU1NAg/ehH0uDBfm8b0ApCGzrVh3V1+tln39YXq3tp10WJOGpNyu5eovUnDtPG/lkaOHyFcpSdkPUCQFtVVFTo3HPP1R577KGHHnpIZhZ0SQBS0YMPSvPm+VP9M70a20FoQ6d6ccNINdy5i4Z88JmiVRsTsodN/foo739W6o97P6PSLFO2FSVirQDQJs45XXLJJVq9erXeffddde3aNeiSAKSir76SbrhB+vrXpW9+M+hqEHKENmzXzLp6fVA7uMOf/79lw9VzVY0i5RUdW4GZcnYboEif7psXbdi9SKN6ztTeucUdrguZycwGSnpCUl/5WbqTnXP3BlsVUs3999+vl156SXfffbcOPvjgoMtBGqA3ZahrrpGqq/2FtNlbjx0gtKFVDS6ic9//nvo9kS+LdGwd3TfUyxZ91uE9bJaXp88vGKgTTv9AWbGTjfTIqdE53T+QRGhDuzVK+qlzbpaZdZU008xec87NC7owpIZZs2bpqquu0mmnnaYf//jHQZeD9EFvyjQzZ0qPPOKPYxs6NOhqkAIIbVBNtF51rlGRraLVJucUXVKsgr9/INfY8ePRoh35kJmy8vNlXYpVO7hed/ebrmxrfvp+Ahvazzm3UtLK2OMqM5svqb8kBkbYoaqqKo0bN06lpaV69NFHOY4NCUNvykAPPSR16SJNmBB0JUgRhLYMV+cadPonZ2npvwfGz5rfJCoNeL9BLtLB3Ww7IWdAf3128W6q26NOF4x4d6vABuw8MxskaYSk6VstHy9pvCTtxqmX0cwPfvADLV68WG+88YZ69+4ddDlIU631pthr9Kd0UFsr/fGP0llnSd26BV0NUgShLcNtco368r0BGjRxuhRNfjhrTaRPiY45bbYeHvBu0KUgDZlZF0kvSLrCObeh+WvOucmSJkvSqFGjEnLuHKS+J554Qk8++aRuvPFGHXvssUGXgzS1vd4k0Z/SxksvSRs2SBdcEHQlSCGEtgzzt5p83bXkRNU0+Oua1TfmqORTSa5DkxgTwnJyFDlyf60b0nSq25p+pjO6fBlYTUhfZpYrPyh62jk3Leh6EG7RaFTTpk3TZZddpmOPPVbXXXdd0CUhTdGbMsgTT0gDBkjHHRd0JUghhLYMc/tnJ6vg2i7qvroytqRe0cqVirrgNthZYaEWnZOr577+m83LCiyiPXIkiWuWIHHMH4T0B0nznXO/DroehFc0GtWLL76oiRMnas6cORo2bJieeuopZWdzXUgkHr0pg6xeLf3979LPfiZlcegH2o7QlgEiLqo59Q1aUL+LlizvpWFLl6px9VdBl6WsggLZwF3V2Luruu1SpdH5uc1ezW31c8BOOFLS+ZLmmNmHsWXXOudeCbAmhEh8z9rEiRM1d+5cDR06VE8//bTGjh1LYENnojdliilTpEhEOv/8oCtBiiG0ZYAN0U361ls/1ICXc7T3ilpF11bu+EPJsPcgfXp1gY7dY5F+Ucqxa+h8zrl/S+KUf9gGYQ1BojdlkCeekA4+WBo+POhKkGIIbRmgQU6Fi/JVNO0dSerwNdN2luXkSM0GPw09i3TevtM1sbQsoIoAZDrCGoCkmTtXmj3bX0wbaCdCG5Iiq6hIa849UGtHNJ3wJKdXra7vSmADkHyENQBJ9+STfuP1uHFBV4IURGhDUlhRoTaeuFGfHPnYFstzjcERgOSJRqN64YUXNGnSJM2dO1f77LOPnnnmGY0ZM4awBqDzRCLS009LJ58s9ekTdDVIQYQ2tEnOgP7aMHqAGgo7NuW+sch0wK6fEtIABCIe1iZOnKiysjLCGoDkevNNafly6e67g64EKYrQhjapGtVfR0yYruM7OJ0xzyIamrtBUpfEFgYA20FYAxAKTzwhlZRI3/hG0JUgRRHaMkCWpIYSp+y995RVVatx9RopGtn2fcXFyupbKpez7UCmqn+OTuw2R8cXbvu5tiOwAUgOwhqA0Ni4UZo2TTr3XKmA68+iYwhtGaAkq0A/OvUV/X30cH363mDt9at6RSrWbvO+TUcPV+X/q1L/kvXbvHZiyTs6MG+DpOIkVAwAHUNYAxA6L74oVVdzbTbsFEJbBsi1bP2wxxL9sMcSja4+W1ZUJK3bNpht7Jej+/d/RkcWZLWyJgIbgHCKRqOaOnWqJk2apLKyMg0bNkxTpkzR2WefTVgDEKwnn5QGD5aOPDLoSpDCCG0Z5uzdZ+mhX5yg7JqB27xWtHelBubUiGmMAFIFYQ1AqC1fLv3jH9KECVJWaxvFgR0jtGWYn/RYqB+cMb/F17LNlG8ENgDhR1gDkBKeeUZyTvrOd4KuBCmO0JZhsi1LRZYXdBkA0CHxsDZx4kTNmzePsAYgvJyTHn9cOvxwaciQoKtBitvhfloze8TMvjKzuc2W9TSz18xsYey+R2y5mdlvzGyRmX1sZiM7s3gAQOaYM2eO9t9/f40dO1bOOU2ZMkVz5szRuHHjCGwAwufDD6WyMumCC4KuBGmgLZNrH5N00lbLrpb0unNuiKTXY88l6WRJQ2K38ZIeSkyZAIBMVldXp3HjxqmiooKwBiA1PPmklJcnjRkTdCVIAzsMbc65tyVtfX740yU9Hnv8uKQzmi1/wnnvSepuZv0SVSwAIJzeeOMNLViwoNPWP2nSJM2bN0+PPvooYQ1A+DU2+uPZTjtN6tkz6GqQBjp6Gpu+zrmVscerJPWNPe4vaWmz9y2LLduGmY03sxlmNmNNxc5csBkAEKSlS5fqlFNO0UUXXdQp658xY4buuOMOXXzxxTr55JM75TsAIKFee01avZprsyFhdvpEJM45Z2auA5+bLGmyJI06sKDdnwcAhMOkSZNUV1en6dOn66OPPtKBBx6YsHXX1dXp4osvVt++ffXrX/86YesFgJ1WWystWyZFIv4WjTY9fughv4ftlFOCrhJpoqOhbbWZ9XPOrYxNf/wqtny5pOYXABsQWwYASEOffvqpHn30UZ1//vl6/vnn9bvf/U73339/wtZ/8803a+7cufrLX/6i7t27J2y9ALDTTjlFeuut1l+//HJ/TBuQAB0NbS9JulDS7bH7PzdbfrmZPSvpUEnrm02jBACkmQkTJqigoEB33nmnnHN68skndccdd6i4uHin1z1r1izddtttuvDCC3XqqacmoFoASJBoVJo+3R+zdu65Una2v2Vl+fvcXOnoo4OuEmlkh6HNzKZIOk5SbzNbJukG+bD2vJl9V9ISSfHT4rwi6RRJiyTVSLq4E2oGAITArFmz9Pzzz+u6665Tnz59dOmll+qpp57S888/r4sv3rn2X19fr4suukh9+vTR3XffnaCKASBBPv/cT488/XTpnHOCrgYZYIehzTnX2t/E41t4r5P0g50tCgAQfr/85S/Vs2dPXXXVVZKkI488UsOGDdPDDz+806Ht5ptv1pw5c/TSSy+pR48eiSgXABKnrMzf77dfsHUgY3T07JEAgAz29ttv629/+5uuvvpqlZSUSJLMTOPHj998QpKOmjVrlm699Vadf/75+sY3vpGokgEgceKhbfjwYOtAxiC0AQDaxTmna6+9Vrvuuqsuv/zyLV674IILlJ+fr8mTJ3do3fX19br44otVWlqqe+65JxHlAkDilZVJAwdK3boFXQkyBKENANAur7zyiv7zn//o+uuvV2Fh4Rav9ezZU2effbaeeuopVVdXt3vdt956qz7++GM9/PDD6skFaQGE1dy50r77Bl0FMgihDQDQZtFoVL/85S+155576pJLLmnxPZdeeqk2bNig5557rl3r/vDDD3XLLbfovPPO0ze/+c1ElAsAiReJSAsWcDwbkorQBgBos+eee04fffSRJk2apNzc3BbfEz8hSXumSDY0NOiiiy5Sr169dO+99yaqXABIvMWLpbo69rQhqTp6nbaEmvlxXXl2v0XVksqDrqWDeovag0DtwWhr7bt3diFIroaGBk2YMEEHHHCAxo0b1+r7zEyXXnqprrjiCn300Uc68MADd7ju2267TR999JFefPFF9erVK5FlA0BixU9CQmhDEoUitDnnSs1shnNuVNC1dAS1B4Pag5HKtWPnPPLII1q8eLFefvllZWVtf6LG+eefr1/84heaPHmyHnjgge2+96OPPtJNN92kc845R2eccUYiSwaAxIuHtmHDgq0DGYXpkQCAHaqtrdWkSZN0xBFH6NRTT93h+9t6QpKGhgZdfPHF6tmzp37zm98ksmQA6Bxz50qDBkldugRdCTIIoQ0AsEMPPPCAVqxYodtuu01m1qbPtOWEJHfccYdmz56thx56SL17905UuQDQecrKOAkJki5Moa1jF/UJB2oPBrUHI5VrRwesX79et912m0466SQdc8wxbf7cjk5IMmfOHE2aNEljx47VmWeemahyAaDzNDRIn3zC8WxIutCENudcyg4EqT0Y1B6MVK4dHXPXXXdp7dq1uuWWW9r1ufgJSaZPn66PPvpoi9fiZ4vs3r277rvvvkSWCwCdZ9EiH9wIbUiy0IQ2AED4fPXVV/r1r3+ts88+WyNHjmz3588//3zl5+dvs7ftV7/6lWbNmqUHH3xQpaWliSoXADoXZ45EQAhtAIBW3Xrrrdq0aZNuuummDn2+Z8+eGjNmzBYnJJk7d65uvPFGjRkzRt/+9rcTWS4AdK65cyUzaZ99gq4EGSYUoc3MTjKzT8xskZldHXQ922NmA83sTTObZ2ZlZvbj2PKeZvaamS2M3fcIutaWmFm2mc02s7/Eng82s+mx3/45M8sLusaWmFl3M5tqZgvMbL6ZHZ5Cv/mVsb8rc81sipkVhPV3N7NHzOwrM5vbbFmLv7N5v4n9GT42s/bvhkGoLVmyRA899JAuuugiDR06tMPrGT9+/OYTkjQ2Nuriiy9WSUmJ7r///gRWCwBJUFYm7bmnVFQUdCXIMIGHNjPLlvSApJMlDZd0jpkND7aq7WqU9FPn3HBJh0n6QazeqyW97pwbIun12PMw+rGk+c2e3yHpbufcXpLWSfpuIFXt2L2S/uac20fSgfJ/htD/5mbWX9KPJI1yzu0nKVvSOIX3d39M0klbLWvtdz5Z0pDYbbykh5JUI5Jk4sSJMjPdcMMNO7We+AlJHn74Yd15552aMWMG0yIBpKayMqZGIhCBhzZJoyUtcs595pyrl/SspNMDrqlVzrmVzrlZscdV8uGhv3zNj8fe9rik0F0h1swGSDpV0u9jz03S1yRNjb0lrHWXSDpG0h8kyTlX75yrVAr85jE5kgrNLEdSkaSVCunv7px7W9LarRa39jufLukJ570nqbuZ9UtOpehsCxYs0OOPP67LLrtMAwcO3Kl1xU9I8v7772vChAn69re/rbPPPjtBlQJAktTXSwsXEtoQiDCEtv6SljZ7viy2LPTMbJCkEZKmS+rrnFsZe2mVpL4BlbU990j6uaRo7HkvSZXOucbY87D+9oMlrZH0aGxq5+/NrFgp8Js755ZLulPSl/Jhbb2kmUqN3z2utd85Zf/fxY5NmDBBRUVFuuaaaxKyvvgJSUpKSvTAAw8kZJ0AkFSffio1NhLaEIgwhLaUZGZdJL0g6Qrn3IbmrznnnCQXSGGtMLPTJH3lnJsZdC0dkCNppKSHnHMjJFVrq6mQYfzNJSl2/Nfp8sFzV0nF2nb6YcoI6++MxJo5c6amTp2qn/zkJwmbwtizZ089/fTT+vOf/6w+ffokZJ0AkFRzY4d7c2FtBCAn6AIkLZfUfO7NgNiy0DKzXPnA9rRzblps8Woz6+ecWxmbIvZVcBW26EhJ3zSzUyQVSOomf5xYdzPLie31Cetvv0zSMufc9NjzqfKhLey/uSSdIOlz59waSTKzafL/LVLhd49r7XdOuf930TbXXnutevXqpZ/+9KcJXe9ZZ52V0PUBQFKVlUnZ2dJOnJgJ6Kgw7Gn7QNKQ2Nn08uRP0vBSwDW1KnYc2B8kzXfO/brZSy9JujD2+EJJf052bdvjnLvGOTfAOTdI/jd+wzl3nqQ3JcXPuR26uiXJObdK0lIzi3fJ4yXNU8h/85gvJR1mZkWxvzvx2kP/uzfT2u/8kqQLYmeRPEzS+mbTKJGi3nrrLb366qu65ppr1K1bt6DLAYDwKCuT9tpLys8PuhJkoMD3tDnnGs3sckl/lz+z3iPOubKAy9qeIyWdL2mOmX0YW3atpNslPW9m35W0RNKYgOprr19IetbMbpY0W7GTfYTQDyU9HQv2n0m6WH6jQ6h/c+fcdDObKmmW/JlHZ0uaLOmvCuHvbmZTJB0nqbeZLZN0g1r/u/2KpFMkLZJUI//fBCnMOadrrrlG/fv312WXXRZ0OQAQLmVlTI1EYAIPbZLknHtFfgAYes65f0uyVl4+Ppm1dJRz7i1Jb8UefyZ/Bs9Qc859KGlUCy+F/jd3zt0gH36aC+Xv7pw7p5WXtvmdY8e3/aBzK0Iyvfzyy3rvvfc0efJkFRYWBl0OAITHpk3SokXS2LFBV4IMFYbpkQCAgEUiEf3yl7/UkCFDdNFFFwVdDgCEy4IFUjTKnjYEJhR72gAAwXr22Wc1d+5cTZkyRbm5uUGXAwDhUhY7cofT/SMg7GkDgAxXX1+v66+/XgcddJDGjAndoaEAELyyMiknRxoyJOhKkKHY0wYAGe4Pf/iDPvvsM/31r39VVhbb8gBgG2Vl0t57S3l5QVeCDMW/zgCQwWpqanTTTTfpqKOO0sknnxx0OQAQTpw5EgFjTxsAZLD77rtPK1eu1PPPPy9/KUEAwBZqaqTPPpMuuCDoSpDB2NMGABmqsrJSd9xxh0455RQdddRRQZcDAOE0f77kHCchQaAIbQCQoX71q19p3bp1uuWWW4IuBQDCizNHIgQIbQCQgVavXq177rlHY8eO1UEHHRR0OQAQXmVl/gQke+0VdCXIYIQ2AMhAt9xyi+rq6nTTTTcFXQoAhFtZmbTPPv6U/0BACG0AkGG++OIL/fa3v9Ull1yiIVxzCAC2b+5cpkYicIQ2ABnFzE4ys0/MbJGZXR10PUG48cYblZWVpeuvvz7oUgDE0JtCauNGackSQhsCR2gDkDHMLFvSA5JOljRc0jlmNjzYqpJr3rx5evLJJ3X55ZdrwIABQZcDQPSmUJs3z98T2hAwQhuATDJa0iLn3GfOuXpJz0o6PeCakuq6665TcXGxrr6aDflAiGR8bwqt+JkjubA2AkZoA5BJ+kta2uz5stiyzcxsvJnNMLMZa9asSWpxna26ulqLFy/WVVddpd69ewddDoAmO+xNUnr3p9AqK5MKCqTBg4OuBBmO0+AAQDPOucmSJkvSqFGjXMDlJFRxcbFmz56thoaGoEsB0AHp3J9Ca+5cadgwKTs76EqQ4QhtADLJckkDmz0fEFuWMbKyspSfnx90GQC2lPG9KbTuuENavz7oKgBCG4CM8oGkIWY2WH5ANE7SucGWBAD0ptA68MCgKwAkEdoAZBDnXKOZXS7p75KyJT3inCsLuCwAGY7eBGBHCG0AMopz7hVJrwRdBwA0R28CsD2cPRIAAAAAQozQBgAAAAAhRmgDAAAAgBAjtAEAAABAiBHaAAAAACDECG0AAAAAEGKENgAAAAAIMUIbAAAAAIQYoQ0AAAAAQozQBgAAAAAhRmgDAAAAgBAjtAEAAABAiBHaAAAAACDECG0AAAAAEGKENgAAAAAIMUIbAAAAAIQYoQ0AAAAAQozQBgAAAAAhRmgDAAAAgBAjtAEAAABAiBHaAAAAACDECG0AAAAAEGKENgAAAAAIMUIbAAAAAIQYoQ0AAAAAQsycc0HXAAChZGZrJC1J8Gp7SypP8DoTjRoTgxoTozNq3N05V5rgdSZVJ/SnTP27kGipUKOUGnVmYo2t9iZCGwAkkZnNcM6NCrqO7aHGxKDGxEiFGtNBKvzO1Jg4qVAnNW6J6ZEAAAAAEGKENgAAAAAIMUIbACTX5KALaANqTAxqTIxUqDEdpMLvTI2Jkwp1UmMzHNMGAAAAACHGnjYAAAAACDFCGwAAAACEGKENAJLEzE4ys0/MbJGZXR10PVszs4Fm9qaZzTOzMjP7cdA1tcTMss1stpn9JehaWmNm3c1sqpktMLP5ZnZ40DVtzcyujP13nmtmU8ysIAQ1PWJmX5nZ3GbLeprZa2a2MHbfI8ga0xG9KXHC3p/oTR2uKfDeRGgDgCQws2xJD0g6WdJwSeeY2fBgq9pGo6SfOueGSzpM0g9CWKMk/VjS/KCL2IF7Jf3NObePpAMVsnrNrL+kH0ka5ZzbT1K2pHHBViVJekzSSVstu1rS6865IZJejz1HgtCbEi7s/Yne1DGPKeDeRGgDgOQYLWmRc+4z51y9pGclnR5wTVtwzq10zs2KPa6S/8e8f7BVbcnMBkg6VdLvg66lNWZWIukYSX+QJOdcvXOuMtiqWpQjqdDMciQVSVoRcD1yzr0tae1Wi0+X9Hjs8eOSzkhqUemP3pQgYe9P9KaOC0NvIrQBQHL0l7S02fNlCuGgI87MBkkaIWl6sJVs4x5JP5cUDbqQ7RgsaY2kR2PTpH5vZsVBF9Wcc265pDslfSlppaT1zrlXg62qVX2dcytjj1dJ6htkMWmI3pQ4Ye9P9KbESmpvIrQBALZgZl0kvSDpCufchqDriTOz0yR95ZybGXQtO5AjaaSkh5xzIyRVK2RT+mLHXpwuP4jbVVKxmX0n2Kp2zPnrFHGtogwV1t4kpUx/ojd1kmT0JkIbACTHckkDmz0fEFsWKmaWKz8oeto5Ny3oerZypKRvmtkX8lO4vmZmTwVbUouWSVrmnIvvCZgqP1AKkxMkfe6cW+Oca5A0TdIRAdfUmtVm1k+SYvdfBVxPuqE3JUYq9Cd6U2IltTcR2gAgOT6QNMTMBptZnvyB1S8FXNMWzMzkj3WY75z7ddD1bM05d41zboBzbpD87/eGcy50W2Cdc6skLTWzobFFx0uaF2BJLflS0mFmVhT77368QnZCgmZeknRh7PGFkv4cYC3piN6UAKnQn+hNCZfU3pTTmSsHAHjOuUYzu1zS3+XPhvWIc64s4LK2dqSk8yXNMbMPY8uudc69EmB3Jzq5AAAgAElEQVRNqeqHkp6ODYI/k3RxwPVswTk33cymSpolf2a+2ZImB1uVZGZTJB0nqbeZLZN0g6TbJT1vZt+VtETSmOAqTD/0poxDb+qAMPQm81MwAQAAAABhxPRIAAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDTvNzB4zs5tjj482s086uJ7fmtmExFYHIFPRmwCEFf0J7UVoyxBm9oWZ1ZrZRjNbHWsWXRL9Pc65fznnhrahnovM7N9bffb7zrmbEl2TmV1oZjPNbIOZLTOz/zWznER/D4D2y/DeNM7MPjGz9Wb2lZk9bmbdEv09ADomk/vTVt/7upk5xk7BIrRllm8457pIGilplKTrtn5Dmv4PWSTpCkm9JR0q6XhJVwVaEYDmMrU3/UfSkc65Ekl7SMqRdHOwJQHYSqb2J0mSmZ0nKTfoOkBoy0jOueWS/k/SfpIU23ryAzNbKGlhbNlpZvahmVWa2TtmdkD882Y2wsxmmVmVmT0nqaDZa8eZ2bJmzwea2TQzW2NmFWZ2v5kNk/RbSYfHtl5Vxt67eapA7Pn/mNkiM1trZi+Z2a7NXnNm9n0zWxir8QEzs1b+vA/FtmLVx/7sT0s6MhG/JYDEycDetNQ5V95sUUTSXjvzGwLoHJnWn2LvL5F0g6Sf7+zvh51HaMtAZjZQ0imSZjdbfIb8XqjhZjZC0iOSLpXUS9LDkl4ys3wzy5P0J0lPSuop6Y+Szmrle7Il/UXSEkmDJPWX9Kxzbr6k70t61znXxTnXvYXPfk3SbZLGSOoXW8ezW73tNEmHSDog9r6vt/EnOEZSWRvfCyBJMrE3mdlRZrZeUlWs3ntaey+A4GRif5J0q6SHJK3aznuQJIS2zPKn2JaZf0v6p/z/jHG3OefWOudqJY2X9LBzbrpzLuKce1xSnaTDYrdcSfc45xqcc1MlfdDK942WtKuknznnqp1zm5xz/27lvVs7T9IjzrlZzrk6SdfIb10a1Ow9tzvnKp1zX0p6U9JBO1qpmV0iP73hzjbWAaDzZWxvcs79OzY9coCkX0n6oo11AEiOjOxPZjZKflbSfW38bnSytJ2Dixad4Zz7RyuvLW32eHdJF5rZD5sty5NvIk7Scueca/baklbWOVDSEudcYwdq3VXSrPgT59xGM6uQ3+L0RWxx8y0/NZK2e3CwmZ0hvwXqhK2mJAEIVkb3pth6lpvZ3+S3io/sQF0AOkfG9Sczy5L0oKQfO+catzODEknEnjbENW8kSyXd4pzr3uxW5JybImmlpP5bzYHerZV1LpW0m7V8gK5rYVlzK+QboCTJzIrlpxss39EfpCVmdpKk38kfUDynI+sAEIi07k1byZG0ZwLWAyA50rU/dZOflfScma1S017BZWZ2dDvXhQQhtKElv5P0fTM71LxiMzvVzLpKeldSo6QfmVmumZ0pvyu/Je/LN6rbY+soMLP4CUBWSxoQm+fdkimSLjazg8wsX346wnTn3Bft/cPE5ng/Leks59z77f08gNBIt950npntFnu8u6RbJL3e3vUACIV06k/r5ffaHRS7nRJbfrCk6e1cFxKE0IZtOOdmSPofSfdLWidpkaSLYq/VSzoz9nytpLGSprWynoikb8ifDe1LScti75ekN+RPBrLKzLaZqhibijBB0gvyzWtPSeM6+EeaIKlE0iuxMy5tNLP/6+C6AAQkDXvTcEnvmFm1/On/P4n9+QCkmHTqT85bFb9JWhN7aXXsz4IA2JbTawEAAAAAYcKeNgAAAAAIMUIbAAAAAIQYoQ0AAAAAQozQBgAAAAAhFoqLa/fu3dsNGjQo6DIAJNDMmTPLnXOlQdexM+hNQHqiPwEIo+31plCEtkGDBmnGjBlBlwEggcxsSdA17Cx6E5Ce6E8Awmh7vYnpkQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAgxQhsAAAAAhBihDQAAAABCjNAGAAAAACFGaAMAAACAECO0AQAAAECIEdoAAAAAIMQIbQAAAAAQYoQ2AAAAAAixnQptZvaImX1lZnObLetpZq+Z2cLYfY+dLxMA2o7eBCCM6E0AOmpn97Q9JumkrZZdLel159wQSa/HngNAMj0mehOA8HlM9CYAHbBToc0597aktVstPl3S47HHj0s6Y2e+o70aG6XhwyUzqWtX6bTTpDvvlD74wL8GIP2FsTdJ0tSpvjeZSSNHSldeKf3pT1JFRbIrARCEsPamVauk7Gzfm/r1k8aNkx58UCork6LRZFcDoCU5nbDOvs65lbHHqyT1belNZjZe0nhJ2m233RL25Q0N0vz5/vHGjdJf/+pvcfvsIw0a1HQbPLjpcWmpb1gA0lKgvUmSli5tejx7tr/dc0+suL7SXnu13J8GDpTy8hJaCoDwaFNvkjqvP9XVNYWzVauk557zt7gDDtiyNzXvUd27J6wMANvRGaFtM+ecMzPXymuTJU2WpFGjRrX4no4oLJRcbG1r1khvv+1v//ynlJ/vBz9ffOH3vG29dbuwsOUwF3/eu3eiqgQQpCB6k+T3rF15pVRfL82c6fvS22/7xyef7HvTf/4jPfusFIk0fc5M6t+/9f60225STqd2cwDJsL3eFHu9U/rT7rv7sZNz0pdf+t4Uv+2xhx8fffGF9OabUlXVlp8tKWk5zMXvu3VLVJVAZuuMf+ZXm1k/59xKM+sn6atO+I42KS2VzjrL31pSVSUtWeIb0eef+/v4bfp0ae1WExgGDJCOOEI6/HB/GzGCrd9ACglNb8rLa+ojV7dw9Epjo7R8eVM/at6f/vUv6ZlntpyyVFgoHXKIX1+8R5WWJufPAmCnhaY3mfkAd8EF/rY156R167YcL8V71OLF0j/+IVVXb/mZvffecuw0fLifigmgfTojtL0k6UJJt8fu/9wJ35EQXbtK++3nby3ZsMGHungzev996d13peef96/n50ujRm05UNpll+TVD6BdUqY35eT4gdPuu0vHHrvt6w0NTaHu88+ljz+W3nlH+vWvpTvu8O/Zc8+mvnTEEb7PMVACQillepOZ1LOnv40cue3rzvkN3vEw9+mn0nvv+cNUHnvMv6dbN+nQQ5t606GHMsUSaAtzruN7181siqTjJPWWtFrSDZL+JOl5SbtJWiJpjHNu64NutzBq1Cg3Y8aMDteRbCtW+PD27rt+oDRzpp/uJPnpAM23KB1wgJSbG2i5QCDMbKZzblRA352Rvam2Vpo1y/eleH9avdq/1qWLNHp0U3867DA/8AIyUVD9KVG9SUqt/uSc3/jdfOw0Z46fMWDm977Fx01HHOH3zmVxJWEkiXNO0ZqoItURRTZGtriPVke3WRbZGNEuF+yi4n2LE17L9nrTToW2REmlxtOSujo/UGrejFas8K8VFW07bYlj45AJggxtiZLqvck5v7U73pfefVf66KOm4+X22WfLgdKwYQyUkBnoT8GrqmqawRS/rVvnX+vRw29Yio+bRo/2s6OAHYnWR1W/ul71K+u1/L7lWv3UanU5uIsKBha0GMoiGyOK1kSldsQhyzMNf264Ss9I/HEIhLYkc86fJa75QGn27KZLDuy115Z745i2hHTEoCicqqv9iZiab2SKn5SppMRPVYr3p0MP9cuAdEN/Cp9o1E+njI+b3n3XX3JA8huT9t9/y41Me+7JGb8zjXNOdcvqVF1WrdpPalW3ok71K31Aq19Vr7qVdWqsaPn6XsX7Fyu7OFvZXbKVVZyl7C7Z/nlsWYuvtXCfVZylrJzO27pJaAuBmho/jbJ5kPsqdqhx167S174mnXmm9I1v+C1MQKpjUJQanJMWLdpyoDRnjl9u5qd4n3GG70/7788gCemB/pQaKiv9ieHiY6fp0/35BiR/sqWTT5a+9S3pxBP9zCakB+ec6lfWq3putarL/K2mrEbV86oV2dB0amXLN+X3y1feLnnK65e3zX1+v3zlluYqf0C+LCs1/vEitIWQc9Jnn/lG9J//SC+/7E8skJMj/dd/+QHS6af7i1wCqYhBUerasKFp2tKrr/oe5Zzfsn3mmX6QdOihTKXEthoiDaqqr1JVXZU21G1QVX3svq6q5cfbeX3W+Fka2ntop9RJf0pNkYg0b57vTW+/7U9wUlnpA9vJJ/v+dOqpzBBor4Z1DapZULM58GQXJGf6l3NODV81+GC2VUBrrGzaY5bbO1fF+xWraN8iFe9brOJ9i1U0rEi5vXNlabYlkdCWAqJRacYMado0f1u40G/RPvzwpkHSHnsEXSXQdgyK0sfq1dKf/+x70+uv+6ne/fr5vnTmmdIxx3DCpe1pjDbqX0v+pYN3PVjd8lP3olX1kXqV15RrTfUa3TP9Hj324WOSpD167LE5aG1q3NSmdRXmFKprfld1zeuqbvnd1DU/dp/XtOzKw6/Url137ZQ/C/0pPTQ0SG+9Jb34or+tWuV70fHHN2387tMn6CrDr+KvFZpz2pzNz3O652y55yr2OL9f/hbLG9c2asP7G1T9cbU/aUd9VK7eNd3XbfW8PqpoXVSRqoga1zcqsj4i19iUQ3J65jSFsmYBLa9P5lxfi9CWYpzzW5LiAe7DD/3yAw/0TejMM6V992WaEsKNQVF6qqz0W7enTZP+7//8GSt79JC++U3fm/77v/1149Bk9srZGjl5pEymYaXDNLr/aB3a/1CN7j9a+/fZX7nZwSfe9ZvWa375fM1fM1+fVnyq1dWrfUCrWaM11Wu0pmaNNtRtaPGz5+1/3hbhq8UgttXjnKxgrwZPf0o/0ai/vMCLL/r+9NlnfjbAUUf5DUzf+pa/jAq2VV9er6oPqjYfG1a/0h8f1vx5tDba6uct15RdnC3LM2XlZ/n7vKzNzzc/jt1nd81WTkmOckpylNc3b3NAy9slL+32nLUXoS3Fff55UxN65x0f6vbaqynAHXII05QQPgyK0l9NjZ8+OW2an+JdWSkVFzdNUzrlFKYpSVJ1fbX+/eW/9f7y9zV9+XRNXz5d5TXlkqSCnAKN7DdSo3cdrdH9/W2PHnvIzFRRU6EvKr9Q1/yu6lnYU90Lurc77DjntG7TOq3auKrF27INy7SgfIFWbly5+TM5WTnqU9xHpUWlKi0uVe+i3v5x7Hn8vkdBDw3pNUQFOQUJ/b2Sgf6U3pzz16+cNs2Pn+bEdiIdfHBTgBs2jI3fbeWcU2RDZPPJPuIn/8jukq2uo7uqeN9iZeUyEE0EQlsaWbWqaZrSG2/4aUo9evjpScceKx13nD9xQCafjbKi4hUtWXKrunQ5QMXFB8Tu91NOTupOS0pFDIoyS339ltOUVq/2G5MOPripNx11FCFO8gOgLyq/0PvL398c5GaunLl5amGvwl7KycrR6urV23y2JL9EPQp7qGdhz6ZbQc/Ny3KycrSwYqE+qfhEi9Yu0sqNK1Ufqd9mPfnZ+dqlyy7q17WfhvYaqmG9h2lY6TAN6z1Mg3sMDnxPWGejP2WWhQubetN77/ll/fs39aZjj5WGDCHEIXiEtjS1bp30yis+vP3zn/7ClZIfFMVD3LHHSgcd5E9wkikqKl7Rl1/ero0bP1Yksn7z8oKCwc1CnL8vLNxTZhmccDsRg6LMFYn4gdHf/uZ70/TpPtRlZUkjRjT1pqOP5my5cQ2RBpWtKdP0ZdP1/vL3FVVU+5buqz167KGahhqtrV2rdbXrtLZ2rdZuWuvvmy+rXauI82dV65bfTUN7DdWQXkM0oOsA7dJll80BLf64JL8ko6ch0Z8y1/LlfmbAW2/52+rYtpF+/Zp603HHSUOHEuKQfIS2DLFsmR8gvfWWv1+40C/v1s1v4Y5vTRo5svUQF41K69f76zbFb2vXNj2urvbHqxQX+1tR0baPW1rW2vc5J5WX+7nnixdLS5b4g4i7d/fhs3v3plv8eV4bj0d1zqmubqk2bvxY1dUfb76vqflEkp+bnZVVqOLi/VRcvK/y8wcoL29X5eX1UU5O99itR+y+hHDXTgyKEFdb60NcvDe9955UV+cHRAce2NSbjjlG6tmz9fXU1GzZj5r3p3Xr/AyD9vSl4mIpP7/1gdmmTX56+uLF/rZxY8s9KX4rLg5ukOecU1V9leoj9epV2CujA1lb0J8g+THIp59uOXZascK/1rfvliFue9MpGxt9D9p6zBR/XFfXvr5UVORvrc2aikallSubxk7Ll/v3tzZuKinJrI33qYzQlqFWrPANKN6MPvnEL+/SxYe4Pn1aHvhEWznW1MwHttpa3+jaIy9v2yYVv+xBVVX71lVY2NSI+vXzexrbIxKpVU3N/FiI+0gbN36smpoFqq9fpXiYa0l2drcWwlx35eb2UG5uH/XufbqKi4e3r5g0xqAIrdm0ye99i/emd9/1y8z8teBGjPABaev+tGk7JyYsKPC9q37bmYDblZXVNECKD5gKCvyAaPny9q0rO3vLQdLtt/vrRyF86E9oSfy6lc3HTsuW+ddKS/3sgIKCbYNZZWXr68zO9huHamraX09+/rahbtMmP3baXj9sSZcuTf3pyCOlhx9ufz3ofIQ2SPLHw739tm9Cb7/tB0W9evkt283vW3vcvbtvPs75rUbV1b4JVVd37LEkDRrkr/0Uvw0a5KdWVVb62/r123+clSU9+2xifp9otFENDavV0FChxsZKNTaui91XqqFh3TbLmj+ORHzy7Nr1EJWWnqUuXQ5W164jlJvbKzHFpSAGRWirujrpgw+atnTPm+f7TXv6U0HsXBiNjTvXl2pq/K1v36a+tMce/r5bN997dtSX4o9/8Qu/gQzhQ39CWzjn97bHe1P8mpVt6Unxx926+bGKc36j986OnfLytuxLe+4pDRjgQ1xbxk2Vlf74vdtvD/rXRUsIbUAnq69frdWrn9GqVY+puvrjzcvz83dTly4j1LXrCHXp4m/5+QMyYuoSgyIAYUV/AhBG2+tNzHAFEiAvr68GDrxSAwdeqYaGClVVzdbGjf5WVTVLFRUvSfIbSHJze6u4eD8VFg5RYeFeKizcS/n5A5Wb21u5uaXKzi7OiFAHAACAtiG0AQmWm9tLPXueoJ49T9i8rLFxY+xkKD7E1dTMV3n5n9TQsGabz5vlxwJcb+XllSo3t7eysorUvfux2mWXC5L5RwEAAEAIENqAJMjJ6aKSkiNUUnLEFssbG9ertnaR6upWqKGhPHZb0+xxuaqqZqqxcZ1WrXpEeXn9lJ1dpKysImVlFcYeN92bcXFLAACAdENoAwKUk1Oirl0PVteuB7f6nlWrntCCBRdKkj7+ePunojPL3ybIZWUVtbps0KCJysnpmtA/EwAAABKL0JaGfv5zf7ai664LuhIkQt++56tbt0MViWxUJFKraLRG0WitIpEaRaM1bV5WX79hq2W12n3364P+4yGDvPGG9MAD0oMP+rMzAkBYjB0rnXaadP75QVcCtIzQloZee00aODDoKpAoZqaioqFBlwHstEWLpGnTpHvvDboSAGjinDR1qrTXXkFXArSOA2DSUG2tvwA1AIRJba2/pz8BCJOGBikapTch3AhtaYjQBiCMNm3y9/QnAGFCb0IqILSlIUIbgDCK72krKAi2DgBojlkASAWEtjREaAMQRrW1Un6+lMW/PABChNCGVMA/nWmI0AYgjOhNAMKI0IZUQGhLMw0NUiRC4wEQPoQ2AGFEaEMqILSlGRoPgLAitAEII8ZOSAWEtjQTPwMSB/oDCBtCG4Aw4iRJSAWEtjTD1iIAYUVoAxBGjJ2QCghtaYbGAyCsCG0AwoixE1IBoS3N0HgAhBWhDUAYMXZCKiC0pRkaD4CwIrQBCCPGTkgFhLY0Q+MBEFabNtGbAIRP/CRu9CeEGaEtzRDaAIQVe9oAhBFjJ6QCQluaofEACCtCG4Awqq2VzKT8/KArAVpHaEszNTX+noERgLCpqaE3AQifmhp/jTazoCsBWkdoSzMVFf6+V69g6wCA5mpr/cCI3gQgbCoq6E0IP0Jbmikvl7KzpZKSoCsBgCbxDUq9ewdbBwBsrbyc3oTwI7SlmXjjYRc/gDApL/f3DIwAhA2hDamA0JZmaDwAwojQBiCsGDshFRDa0gyNB0AYEdoAhBVjJ6QCQluaofEACCNCG4AwamiQKivpTQg/QluaIbQBCKPycn+sbY8eQVcCAE3WrvX3jJ0QdoS2NBKN+jO00XgAhE15uQ9sOTlBVwIATZgFgFRBaEsjlZU+uNF4AIQNswAAhBGhDamC0JZGuA4SgLAitAEII8ZOSBWEtjTC1iIAYUVoAxBGjJ2QKghtaYTGAyCsCG0Awig+durVK9g6gB0htKURQhuAMHKO0AYgnMrLpS5dpIKCoCsBto/QlkYIbQDCqLpaqqujNwEIHzYoIVUQ2tJIebmUny8VFwddCQA04UB/AGFFaEOqILSlkXjjMQu6EgBowiwAAGFFaEOqILSlERoPgDAitAEIK8ZOSBWEtjRC4wEQRoQ2AGHF2AmpgtCWRsrLOWUtgPDhlNoAwqiuTqqqojchNXRKaDOzK82szMzmmtkUM+NEqknA1iJgx+hPyVdeLmVlSd27B10JEF70puTjJElIJQkPbWbWX9KPJI1yzu0nKVvSuER/D7bU2CitW0fjAbaH/hSM+CyALOZ2AC2iNwWDqdtIJZ31T2iOpEIzy5FUJGlFJ30PYtat8xewpfEAO0R/SjJmAQBtQm9KMkIbUknCQ5tzbrmkOyV9KWmlpPXOuVe3fp+ZjTezGWY2Y82aNYkuI+PQeIAda0t/ojclHqEN2D7GTsFg7IRU0hnTI3tIOl3SYEm7Sio2s+9s/T7n3GTn3Cjn3KjS0tJEl5FxaDzAjrWlP9GbEo/QBmwfY6dgMHZCKumM6ZEnSPrcObfGOdcgaZqkIzrhe9AMjQdoE/pTAAhtwA7RmwLAmW2RSjojtH0p6TAzKzIzk3S8pPmd8D1ohtAGtAn9KcmcI7QBbUBvCkB5uVRSIuXmBl0JsGOdcUzbdElTJc2SNCf2HZMT/T3YEluLgB2jPyXfhg3+7LaENqB19KZgsEEJqSSnM1bqnLtB0g2dsW60rLxcKiryNwCtoz8lF7MAgLahNyUfoQ2phKvmpImKChoPgPAhtAEIK8ZOSCWEtjTB1iIAYURoAxBWjJ2QSghtaYLGAyCMCG0AwoqxE1IJoS1N0HgAhBGhDUAY1dT4G70JqYLQliYIbQDCqLzcn067a9egKwGAJhUV/p6xE1IFoS0NNDRI69fTeACET3yDklnQlQBAE2YBINUQ2tIAW4sAhBWzAACEEaENqYbQlgZoPADCitAGIIwYOyHVENrSAI0HQFgR2gCEEWMnpBpCWxqg8QAIK0IbgDAqL/fH2vboEXQlQNsQ2tIAoQ1AGEUi0tq19CYA4VNeLvXsKWVnB10J0DaEtjQQD229egVbRypoaJD+8x+prCzoSoD0V1kpRaOEtrZaskR69VXfpwB0LmYBtF1NjfTGG9KXXwZdSWYjtKWB8nJ/DaS8vOR8X1WVVF+fnO/aWc5JixZJDz4onXGGb9BHHSUdcIB0993+dQCdI9kblBoafH9Klf+vq6qkl1+WfvhDaehQadAg6etfl044Qfrqq6CrA9JbeXlyN3avXy81Nibv+3ZGNCrNni397//6ftSjh3T88dJ++0l//nPQ1WWunKALwM5L1taiTZukn/9cuu8+/7yoSOre3f/PvPWtteXx1woLO++6TevW+S1Cr77qb1984ZcPGiSNG+cb0JQp0k9+4pvSww/7egAkVjKnbv/979KFF0qrV/vpTjvqQa0tLymRsjppc2YkIs2YIb32mu9N777rB3GFhdJxx0nf/75UUOB706hR0osvSgcf3Dm1AJmuvNyPC5LxPd/9rvTSS/55164dHzvl53denStWNPWm116T1qzxy/fbT7r8cr/B+5Zb/AbwiROl667rvF6JlhHa0kAyQtv8+T7wfPyxNH68tNtuPhxVVvr7deukpUv96+vWSRs2bH99eXlNjaikxDexbt38ffPHO7ovLvaDnunTm0LaBx/4rURdu0pf+5r0s59JJ54o7blnU1A86yzffK6/3v/Zpk2TBg7s3N8QyDTJCG319dIvfyndeae0777ST3/q+1Lz3rRund94E3+8va3dZr4nxQdJHelL8fucHP+98YHQ66/775ekkSOlq67yvemII7YcjB16qB8YHXWU9PvfS+ed13m/H5Cpysv9xpHO9Oab0ne+47/r6qv9Bpqtx06LFzc9rq7e/voKC5vGTu3tR83vCwr8lMe3327qT/HDRvr08Xv8//u//UbuXXdt+v6TTpIuvVS64Qbpww+lxx/360RyENrSQHm5/5+sMzgn/eEP0o9+JHXpIv31r9Ipp+z4c42NfirA1gOn5rf4axs2+NuqVf6+qsrfRyI7/p6sLL9VvaHBPz70UL/15/GNDQQAACAASURBVMQTpdGjpdzc1j83YYJ04IG+oY4aJU2dKh19dPt+HwCt6+zQtnChdM450syZ0mWX+eC2o73mzvmBUVt6U2Wl70fLlzf1paoqqba2bfUVFPgZCpI0YID0rW/5gdDxx0ulpa1/buRIv0fu7LN9f5o9W7r9dh8CAew85zp3g3dDg3TjjdJtt0l77+3HTgcdtOPP1df7sdOOelN87LR+vd9g3rw/tWV6ePzkK5GI71NHHy1ddJHvT/vv3/oetMJCH9TiG50OO8xPl9xrr7b+MtgZ/BOQBsrLpeHDE7/eykq/V+2Pf/RbW554QurXr22fzcnxc8U7Ol/cOT/YaR7iWruvr/eN47/+y28Zb49vftPvpTv9dL9X7r77/Fakzpq6CWSSzgxtTzzhg1penp9GeMYZbfucmd8A1aWLD1Id0di4474Uvx840G9EGjq0fX2lTx/pH//wUyXvusvPYnj2WX+2OwA7Z+NGP3bojN70+efSuedK773np0Xee6+fFdQWeXl+g872NupsT3yjVFv6k5l07LF+j357DhExk664woe7MWOkQw7xvenrX+9YzWg7Qlsa6IytRe+845vO8uXSHXf4LSrJnLts5ptIYaHUt2/nftewYdL77/spSP/v/0mzZvnw1plzx4FMUFHht+IWFSVunRs2+LD29NPSMcdITz2V/KnNOTlNU5Q6U26u70UjRvjedMgh0p/+5AdLADquszYoPfec39ht5h+PGZPY9e9I841Sbd3I3lHHH+9nBJxxhp+Bddtt/nAUNnp3Hg4hTHG1tX6rSqIaTyQi3XyzHwxlZ/vT4//85+l/sGn37v4g4WuvlX73O7/XbeXKoKsCUlt8g1Ki/hF//30fYKZMkSZN8iccyoRjUS+5RPrnP32/P/xwP5UbQMclOrRVV/u9auPG+WNrP/ww+YEtCIMH+4383/629Itf+I39NTVBV5W+0nwonv4qKvx9IhrPsmV+y8mECdLYsf44iv/f3r3Hx1nWeR//XjOZTM5Nm6TnkrbYNrRQQQuiXcVFfQQ5CbKKCgIe2GfRFV0fXXdlD6zL6npaFg8oK1CUoitYF1BgV+36gD4uUClYWpq0prTpYXJqkiaZmczpev64Ew5tKU0yM9c993zerxcvmtBmvq/Q/jq/+7qu33XGGdP/uqUiHPaGk/zoR17BXbPG2zoJYGrytQsgl/NGT69d621NfOQRr06V06W4Z57pnd1bvdo76/a5z3nfFwCTl8+mbfNmb8rrHXd4Z+ofeaQ4Uyn9orbW2x75xS96q4tr174wtRv5RdNW4vLVtN13nzeUY9Mm75DpXXd5E4bK0Z/8iTeKOxr1VhzvuMN1IqA05aNpO3DAOyvxl3/pnT196invTUE5mjfPm0b34Q9L//RP3pncoSHXqYDSk4/3TtZ659XOPNM7I/bLX0qf/3x5DgwyxqvRP/uZd6bv9NO9WoX8omkrcdN9WpRISB/9qLcnefFi7zzXBz7AnuTVq72rA970Jm9r0sc/7k2DAnD8ptu0Pfig9zDpN7+Rbr3VG4pU6HNkfheNet+LW27x7qY74wxp+3bXqYDSMt33Tr290gUXeAM5zjlHevppbxhauTv3XO+9U0uLN4ny5puPb5oljg9NW4mbTuHZutX7C/9b3/LuNvrtb73RtPA0NUkPPeR9b372M+9JGoDjN9WmbWzMm5p43nnS3LneDoCPfISHSROM8S7i3rjRm/K7ebPrREBp6evztlfPmDH5X/vLX3oPdn/xC+kb3/CGAxX6rtxSsmyZd7Tk/PO9yb7Hc30Tjk8ZLuIGQybj7SHetMn7eDIFw1rvSe0nPuFtgXzoIe9JEY5UUeHd/fS3f1u+20WBydqyxftnYGDyb2ba27271zZvlj72MenLX/YmUOJIb3yjd1cdtQk4PocOeSv227d7D2YnM2QtnfbO0n7pS1Jbm7fSvXp14bKWsvp6acMGb0BLOW4XLRS+lSXqD3+QrrjihY+/9S3pkku8UdDHehp98KD3xHrDBu/uoDvv9J5k49h4UwQcv3e+U+rs9H7893/vTXx861uPPfrfWmndOq9Rq6ryztleeGEx0pY2ahNw/H7xC+9M6ISbb/a2OS5Zcuxf19npPUx6/HFvpP+//Et+rzIJolDIa96QP2yPLFErVki33/7Cx//wD97Zj6VLpeuu85bvDz+D9eij0qmneqPtv/xlb4WNhg1Avm3cKL3qVS98fNFF3orbRRdJt90mdXe/9OcPDXmjoj/4QW/L9u9/T8MGIP8uvti72mfCddd575tWr/YmPz7xxJFTWe++23vv1NHhrdJ95zs0bHDDWB+cEFyzZo3dNLHPD1MSi0k//anXkP3851Iy6e3Vfsc7vDc/7e1eY7dkiXfH0emnu06MoDPG/M5au8Z1jumgNk1fKuU9MLrvPq8+7d7t7QZ43eu8Jq6tTfrkJ6WuLumGG6TPfra8RvnDDeoTJGnnTumBB7z69OijXsM2b563+nb++dKPf+ztSFq7Vlq/XmptdZ0YQXes2kTTFkDxuNe43X+/V4x6e73PX3GF9M1vslyN4uBNEQ5nrXfW7f77vTdJE9/a1lbvafYb3uA2H8oH9QmH6+/3diDdd5/08MPSyIi3xe/6672zbJzNQjEcqzbxWzCAamq8J9gXXeRN7XnsMe9p95vf7DoZgHJmjLcNaWIr0r59Xn06+2ypsdF1OgDlrKlJuvxy75+xMe+S7JYWb2sk4Ac0bQEXDvP0GoA/LVjgDVACAD+JRr17xpB/yb1Jbb9yu1bcukLVJ1a7jlNSGEQCAAAAoOCyh7IaeXpET7/1aY3tG3Mdp6TQtAEAAAAouNqVtVr98Gql+9N6+m1PK9WXch2pZNC0AdOwZ8+X1dd3n+sYAPASY5kxXfuza3Xbk7e5jgIAL9GwpkGnPHCKkruS+v05v1fmUMZ1pJJA0wZMw75931Bv7wbXMQDgJSLhiDr6O3Tdw9dp58GdruMAwEs0ntWoVfeu0ujTo9pywRZlE1nXkXyPpg2Yhmh0vsbG9rmOAQAvETIhrXvnOkXCEV2+4XJlcjzJBuAvTec1qe37bRp6dEhbL92qXCr3yr+ojNG0AdNQWblAqdR+1zEA4AgLGxbqO+d/R4/te0w3PnKj6zgAcIQ5l83R8m8v18EHD+rZDzwrm3V/f7Rf0bQB08BKGwA/e/eqd+uK1Vfo8498Xv+z939cxwGAI8y/Zr6Wfmmpev+9Vx1/1iFradyOhqYNmIZodIGy2UPKZEZcRwGAo/r6uV/XwoaFunzD5RpJUasA+M8Jnz5BJ/z1CTrwbwfU+ZlOGrejoGkDpqGycr4ksUUSgG/NqJqh71/8fXUOdOqTD3/SdRwAOKol/7hE8z86X11f6dK+m9nFdDiaNmAaotEFkqSxMZo2AP71xtY36i/X/qW+u/m7um8715QA8B9jjJbdvEwNZzYo9r2Y6zi+Q9MGTMMLK208EQLgbzf88Q06be5p+vADH1ZshDdEAPzHhIwazmxQ/Nm4bI4tki9G0wZMAyttAEpFZbhS6y9Zr5HUiD543wc5MwLAl2pW1SiXyCn5XNJ1FF+haQOmoaKiXuFwHRMkAZSEk1pO0lfe9hU9tPMh3bLpFtdxAOAItatqJUmjW0cdJ/EXmjZgmrirDUApufb0a3XOq87Rp/7rU9ret911HAB4iZqTaiTRtB2Opg2YJu5qA1BKjDG6/cLbVRup1fs3vF+pbMp1JAB4XqQxosoFlYpvi7uO4is0bcA0RaOstAEoLfPq5+nfLvg3PXngSd3wqxtcxwGAl6hdWctK22Fo2oBpqqycr7Gx/RzqB1BSLj7pYn3otA/pC7/+gh7d/ajrOADwvNpVtUyQPAxNGzBN0egCWZtSOt3vOgoATMpN59ykpTOX6oqfXKGh5JDrOAAgiQmSR0PTBkwTd7UBKFV1lXX6/sXfV9ehLn384Y+7jgMAkrztkZI0uo0tkhNo2oBp4q42AKXs9Yter+vfeL2+9/T3dM/We1zHAQDVtHkTJBPtCcdJ/IOmDZimaNRbaWOCJIBSdf2brtfKlpW66bGbXEcBAFXMrFC4Icz2yBehaQOmqbJyniQxQRJAyYqEI1retFyHxg65jgIAMsaoakkVTduLFKRpM8Y0GmPuNcZsN8Y8a4x5fSFeB/CDUKhSkUgLK20lgvoEHF1NpEaJNFuRXKE2AS9VtbhKiV3UpAkVBfq6/yrpYWvtpcaYSkk1BXodwBe4q62kUJ+Ao6iuqFYiwxskh6hNwItUL6nWwC8GZK2VMcZ1HOfy3rQZY2ZIepOkqyTJWpuSlMr36wB+4t3Vxkqb31GfgJdXXVHNSpsj1CbgSFWLq5QbzSndl1ZlS6XrOM4VYnvkEkm9ku4wxmw2xnzXGFNbgNcBfCMaXcD0yNJAfQJeRk2kRvF03HWMckVtAg5TtaRKkjjXNq4QTVuFpNdIusVae5qkUUmfPfwnGWOuMcZsMsZs6u3tLUAMoHgqK+crne5RLpd2HQXH9or1idqEclUdqdZYdkw5m3MdpRzx3gk4TNXi8aZtF02bVJimba+kvdbax8Y/vldeIXoJa+2t1to11to1LS0tBYgBFI93V5tVKhVzHQXH9or1idqEclVdUS1JSmZ4g+QA752AwzzftLHSJqkATZu1NiapyxizYvxTb5G0Ld+vA/gJd7WVBuoT8PJqIt7cC7ZIFh+1CThSRUOFKmZV0LSNK9T0yD+XtH58+lGnpKsL9DqAL1RUNEmS0mm2q5QA6hNwFNURb6WNYSTOUJuAw1QtrmJ75LiCNG3W2qckrSnE1wb8KB5/VpJUXb3McRK8EuoTcHQT2yMZ++8GtQk4UtWSKsW3svovFehybaDcDA8/rnC4QTU1y11HAYApmdgeyUobAL+oWlyl5HNJWWtdR3GOpg3Ig0OHHld9/ekyhj9SAErTxPZIzrQB8IvqJdXKJXNKdXNtIe8wgWnKZpMaHf29GhpOdx0FAKasNuJdCzaSGnGcBAA8jP1/AU0bME0jI0/J2ozq689wHQUApmxx42JJUudAp9sgADCOC7ZfQNMGTNPw8OOSpIYGmjYApWtBwwLVRmq1vW+76ygAIEmqaqVpm0DTBkzT8PATqqycP37BNgCUppAJaUXzCm3vp2kD4A/h2rAisyNsjxRNGzBtE0NIAKDUtTW3sdIGwFcmJkiWO5o2YBrS6UElEh1sjQQQCG1Nbdo9uJsJkgB8gwu2PTRtwDQMD2+SJIaQAAiEtuY2WVnt6N/hOgoASPKGkSR3J2Vz5X1XG00bMA0TQ0jq69c4TgIA09fW3CZJbJEE4BtVi6tk01Zj+8dcR3GKpg2YhkOHHld19XJFIo2uowDAtC1rWiYjQ9MGwDeql1RLYoIkTRswDcPDT3CeDUBgVFVUacnMJUyQBOAfYe9f2ZGs2xyO0bQBUzQ2tk+p1H4mRwIIFCZIAvCT/gf6FaoKqfGN5b2riaYNmKJDhybOs7HSBiA42pra1N7XrpzNuY4CoMxZa9X3kz7N/F8zFa4Nu47jFE0bMEXDw0/ImArV1Z3qOgoA5E1bc5sSmYS6hrpcRwFQ5oZ/N6yxrjG1XNLiOopzNG3AFB069Lhqa1crHK5yHQUA8oYJkgD8ou8nfVJYarqgyXUU52jagCmwNscQEgCBRNMGwC/6ftKnxrMaFZkVcR3FOZo2YAoSiR3KZg9xng1A4DTXNGtW9SyaNgBOjW4fVfzZOFsjx9G0AVPwwhASJkcCCBZjjDdBkrH/ABzq+0mfJKn5nc2Ok/gDTRswBcPDmxQK1aq29iTXUQAg79qaGPsPwK2+DX2qf129oguirqP4Ak0bMAXpdK+i0fkyprzHzwIIprbmNsVGYhpMDrqOAqAMJbuSGt40rJaL2Ro5gaYNmIJsNq5QqMZ1DAAoiIlhJO197Y6TAChHff8xvjXyYrZGTqBpA6YglxtVOEzTBiCYmCAJwKW+DX2qWVWjmuW815pA0wZMASttAIJsycwlioQiNG0Aii7Vl9LgI4NsjTwMTRswBblcXOFwresYAFAQFaEKLWtaxgRJAEXXf3+/lGNr5OFo2oApyGbjbI8EEGhtzUyQBFB8fT/pU7Q1qrrT6lxH8RWaNmAKstlRtkcCCLS2pjbtPLhT6WzadRQAZSKXzungzw+q+aJmGWNcx/EVmjZgCrztkTRtAIKrrblNmVxGnQOdrqMAKBNjXWOyY1Z1p7LKdjiaNmAKvEEknGkDEFxMkARQbInOhCSpakmV4yT+Q9MGTJK1WVk7xkobgEBb0bxCEk0bgOJJ7kpKkqqXVjtO4j80bcAkZbNxSeJMG4BAa4g2aH79fCZIAiiaZGdSJmIUXRB1HcV3aNqAScrlvKaNlTYAQTerepb2D+93HQNAmUh0JlS1uEomzBCSw9G0AZM0sdLGPW0AgmznwZ16pucZvXXJW11HAVAmkruSnGd7GTRtwCRNrLSxPRJAkN295W4ZGb33lPe6jgKgTCQ6E5xnexk0bcAkZbOjktgeCSC4rLVav2W9zlp8lhY2LHQdB0AZyBzKKNOfUdVSVtqOhqYNmKQXBpGwPRJAMP3uwO/U0d+h95/yftdRAJSJicmRbI88Opo2YJIYRAIg6O76/V2qDFfq0pWXuo4CoExM3NHG9sijo2kDJomR/wCCLJPL6IfP/FDnLTtPjVWNruMAKBPJzvGVNrZHHhVNGzBJuRxn2gAE18ZdG9U92s3WSABFlehMqKKxQpHGiOsovkTTBkwSI/8BBNn6Les1IzpD5y0/z3UUAGUkuSvJKtsx0LQBk8TIfwBBFU/HteHZDbp05aWqquDNE4DiYdz/sdG0AZM0MfI/FKKwAAiWB9of0EhqhK2RAIrK5iwrba+Apg2YpGw2LmMqFQpVuI4CAHm1fst6LahfoLMWn+U6CoAykjqQkk1Zxv0fA00bMEm5XJzzbAACpz/er4d2PqT3nvxehQxvDwAUD+P+XxlVGZikbDbOeTYAgXPPtnuUyWX0/tVsjQRQXIz7f2U0bcAk5XKjjPsHEDjrt6zXypaVevWcV7uOAqDMJHYlJCNVnUDT9nJo2oBJYqUNQNA8N/icfr3n13r/Ke+XMcZ1HABlJtmZVHRRVKFKWpOXw3cGmCTOtAEImru33C1Jet8p73OcBEA5Ytz/K6NpAyYpm42zPRJAYFhrtX7Leq1dtFaLGxe7jgOgDCV3JZkc+Qpo2oBJymZH2R4JIDCe7n5a23q3cTcbACeyiaxS+1MMIXkFNG3AJHnbI2naAATD+t+vV0WoQu9e9W7XUQCUoeRz3uRItkceG00bMEneIBLOtAEofdlcVj945gc691XnqqmmyXUcAGXo+XH/bI88Jpo2YJJYaQMQFI/sfkT7hvexNRKAM4ldXKx9PArWtBljwsaYzcaYnxbqNQAXONNW+qhPgGf9lvWqq6zTBSsucB0FojahPCU7kwrVhBSZHXEdxdcKudJ2naRnC/j1gaLL5TKyNsXI/9JHfULZS2aSunfbvbrkpEtUE+FBlE9Qm1B2Jsb9c0fksRWkaTPGLJR0nqTvFuLrA67kct4SPtsjSxf1CfBs2r9JQ2NDetdJ73IdBaI2oXwx7v/4FGql7SZJn5GUe7mfYIy5xhizyRizqbe3t0AxgPzK5eKSxPbI0nbM+kRtQrlo72uXJJ08+2THSTCO904oO9ZaJTuTjPs/Dnlv2owx50vqsdb+7lg/z1p7q7V2jbV2TUtLS75jAAWRzY5KYqWtVB1PfaI2oVx09HeoMlyp1hmtrqOUPd47oVyl+9LKjmQZQnIcCrHStlbShcaY5yT9UNLZxpi7CvA6QNFlsxMrbZxpK1HUJ2Bce3+7XjXrVQqHwq6jgNqEMpXcxbj/45X3ps1a+1fW2oXW2sWSLpO00Vp7eb5fB3BhYnskK22lifoEvKC9v10rmla4jgFRm1C+Ep2M+z9e3NMGTMILK200bQBKVyaX0R8O/kHLm5a7jgKgjHGx9vGrKOQXt9b+StKvCvkaQDHlcpxpCwrqE8rZc4PPKZ1Ls9LmQ9QmlJPkrqQicyIK17BN+5Ww0gZMwsRKG/e0AShlHf0dksRKGwCnJu5owyujaQMmYWjoEUlSRcVMx0kAYOomxv2vaGalDYA7jPs/fjRtwHHq7d2gffu+oQUL/lzR6HzXcQBgyjr6OzSrepaaa5pdRwFQpnLpnJJ7kqy0HSeaNuA4xOM7tH371aqvf51OPPErruMAwLS097ezNRKAU2NdY1KOISTHi6YNeAXZbEJbt14qYyq0atWPFApVuo4EANPCuH8ArjHuf3IKOj0SCIIdOz6m0dEtOuWUB1VVdYLrOAAwLSOpEe0f3s9KGwCnnh/3z5m248JKG3AMBw7crljsdrW2Xq+mpnNcxwGAaZuYHMlKGwCXkruSMhGj6Pyo6yglgaYNeBkjI09rx46PqrHxLVq8+O9cxwGAvHi+aWNyJACHEp0JVS2ukgkb11FKAk0bcBSZzJC2br1UFRWztHLl3TKGSx8BBEN7X7uMjE6ceaLrKADKGOP+J4emDTiMtVbbt39QicQurVr1I1VWznYdCQDypuNgh1obW1Ud4fA/AHcSuxKqXkIdOl4MIgEOs3fvTerr26ATT/yqZsxY6zoOAORVex/j/gG4NfzksDL9GdWsqnEdpWSw0ga8yNDQb9TZ+Rk1N1+shQs/6ToOAOSVtZZx/wCc233jblU0VmjuB+a6jlIyaNqAcalUj7ZufY+i0Va1td0hYzgYCyBYYiMxjaRGaNoAODO6dVR9G/q04M8XqKKBTX/Hi+8UIO/p87PPXq50uk+vec3/qKJihutIAJB37f3tksT2SADO7P7CboVqQ1p43ULXUUoKK22ApNHRZzQw8HMtXXqj6utPdR0HAAqCcf8AXEr8IaGeH/RowZ8tUKQp4jpOSaFpAyQNDv63JKml5VLHSQCgcNr72lVdUa2FDTzhBlB8e764RyZitPAvqEGTRdMGSBoY2KiqqqWqqmp1HQUACqbjYIeWNS1TyPDXP4DiSnYlFbszpnkfmqfovKjrOCWHqo2yZ21Wg4O/0syZZ7uOAgAF1d7H5EgAbnR9pUuy0gmfOcF1lJJE04ayNzy8WdnskBob/9h1FAAomFQ2pc6BToaQACi6VHdKB249oDlXzFFVa5XrOCWJpg1lb+I8G00bgCDbNbBLWZtlpQ1A0XX9S5dyqZxO+CyrbFNF04ayNzi4UTU1Jykanec6CgAUDOP+AbiQHkhr/7f2a/a7Z6tmeY3rOCWLpg1lLZdLaXDwUTU2cp4NQLAx7h+AC/u+vk/Z4axO+GtW2aaDpg1lbXj4CeVyo5o5k62RAIKtva9ds2tnq7Gq0XUUAGUiM5zR3pv2qunCJtWdUuc6TkmjaUNZGxiYOM/2ZrdBAKDA2vvb2RoJoKj2f3u/MgMZtX6OK5Wmi6YNZW1wcKPq6k5VJNLkOgoAFFRHfwdDSAAUTTaRVddXuzTzbTPVcEaD6zglj6YNZSubTWpo6P9xng1A4A0lh9Q92s1KG4CiOXDbAaW706yy5QlNG8rWoUO/lbVjjPoHEHjPDyFhpQ1AEeRSOXV9qUsz/miGZrxphus4gVDhOgDgyuDgRklhNTa+yXUUACioiXH/TI4EUAzdd3VrrGtMy29dLmOM6ziBwEobytbAwEbV169RRQX7rAEEW0d/h8ImrKUzl7qOAiDgcpmc9nxhj+peW6dZb5/lOk5g0LShLGUyIxoefpxR/wDKQnt/u5bMXKLKcKXrKAACrveeXiV2JtT6uVZW2fKIpg1laWjo17I2wxASAIE3lhnTY3sf4zwbgIKzOas9/7RHNatq1HxRs+s4gULThrI0OLhRxkQ0Y8Za11EAoKD++Tf/rN1Du3Xt6de6jgIg4Pru79PoM6Nq/atWmRCrbPlE04ayNDCwUQ0Nr1c4XOM6CgAUzPa+7brx0Rt12cmX6R3L3uE6DoCA2/vVvapaWqWW97S4jhI4NG0oO+n0gEZGnmTUP4BAy9mcrnngGtVGanXT229yHQdAwMU74hr69ZDm/+l8hSpoMfKNkf8oO0NDj0iymjmT82wAguu2J2/To3se1W0X3qY5dXNcxwEQcLE7Y1JImnMF9aYQaINRdgYGNioUqlZDw+tcRwGAgjgwfECf/vmn9ebFb9bVp17tOg6AgLNZq+7vdWvWObMUnRd1HSeQaNpQdgYHN2rGjD9SKERRARBM1z18nZKZpL5z/ncYuQ2g4AZ+OaCxvWOae/Vc11ECi6YNZSWV6tHo6DOcZwMQWA+0P6B7tt2jv3nT32h503LXcQCUgdi6mCpmVqj5Asb8FwpNG8rK4OCvJInzbAACaXhsWNc+eK1Onn2yPr32067jACgD6cG0+n7Sp9nvm61QlNaiUBhEgrIyMLBR4XC96upe6zoKAOTd9Ruv175D+3TPn9yjynCl6zgAykDvv/cql8xp3tXzXEcJNNphlJXBwY1qbDxLoRDPKwAEy2N7H9PXH/+6Pnr6R3XmwjNdxwFQJmLrYqo9uVZ1r6lzHSXQaNpQNpLJvUokdnCeDUDgpLNpfeSBj2h+/Xzd+JYbXccBUCZGnx3Vof85pLlXzWXoUYGx3ICyMTj435KkxkbOswEIlq/+9qva0rNF//Ge/1BDtMF1HABlInZnTApLcy7nbrZCY6UNZSGbTWrv3n9VJDJbdXWrXccBgLzZeXCnbvi/N+hdJ71LF7Vd5DoOgDKRy+TU/b1uNb2jSZVzOENbaKy0IfCstdqx41qNjPxOJ598n4zhWQWAYLDW6k9/+qeqDFfq5nNvdh0HQBkZ+PmAUgdS3M1WJDRtCLz9+7+jWOwOtbb+jZqbL3QdBwDy5s6n79TGXRt1y3m3aH79fNdxAJSR2B0xVTRVqOm8JtdRygJLDgi0oaHfaufOj2vWrHO1ePHfuY4DAHnTM9qjT/3Xp7R2eavd7AAAE0pJREFU0Vpd89prXMcBUEbSB9Pqu69Pc94/R6FK2oli4LuMwBobi2nr1ncpGl2kk05aL2PCriMBQN7c+MiNGh4b1q0X3KoQ274BFFHPD3tkU5atkUVElUcg5XIpbdv2J8pkhnTyyT9RJDLTdSQAyJuxzJju2nKXLl15qVa2rHQdB0CZid0RU+2ra1V/ar3rKGWDpg2B9Ic//B8NDf1aK1Z8l2mRAALnpx0/1cHEQV356itdRwFQZkaeGdHwpmHNu3qe6yhlhaYNgROLfV/79n1dCxd+UnPmvNd1HADIu3VPr9P8+vl669K3uo4CoMzE1sVkKoxmv2+26yhlhaYNgTI8vFkdHddoxoyztHTpP7uOAwB5FxuJ6aEdD+kDqz+gcIizugCKJ5fOqfuubjWd36TKFu5mKyaaNgRGOt2vrVsvUUVFk1at+pFCoYjrSACQd+t/v15Zm9WVp7I1EkBxHfzPg0p3pxlA4kDemzZjzCJjzH8bY7YZY7YaY67L92sAh7M2q23b3quxsf06+eQNqqxkyR5Hoj6h1Flrte7pdTpz4Zlqa25zHQd5Qm1CqYjdEVNkdkSzzp3lOkrZKcRKW0bSp6y1KyWdKemjxhhGW6Ggdu26XgMDP9eyZd9UQ8MZruPAv6hPKGlPHnhSz/Q8o6tefZXrKMgvahN8L9WXUv8D/Zpz+RyFImzWK7a8f8ettQestU+O/3hY0rOSFuT7dYAJvb0/1p49X9S8eR/R/Pkfdh0HPkZ9Qqlb99Q6RcNRvefk97iOgjyiNqEU9NzdI5u2mnslWyNdKGibbIxZLOk0SY8d5b9dY4zZZIzZ1NvbW8gYCLB4fKe2b79K9fVnaNmyr7uOgxLycvWJ2gS/GsuM6e5n7tbFJ12sxqpG13FQILx3gl/F1sVU95o61a2ucx2lLBWsaTPG1En6saRPWGsPHf7frbW3WmvXWGvXtLS0FCoGAm737htkrdWqVfcqFIq6joMScaz6RG2CX03czcbWyODivRP8auTpEY1sHmEAiUMFadqMMRF5RWe9tXZDIV4DSCQ61d39A82f/79VVbXIdRyUCOoTShV3swUbtQl+FlsXk6k0mvPeOa6jlK1CTI80km6T9Ky19mv5/vrAhD17viRjwlq06C9cR0GJoD6hVHWPdOuhHQ/pitVXcDdbAFGb4Ge5lHc3W/OFzYo0cZ2SK4VYaVsr6QpJZxtjnhr/5x0FeB2UsbGxfYrF7tC8eR9UNDrfdRyUDuoTStL6LeN3s72au9kCitoE3+p/sF/pvrTmXsXWSJcq8v0FrbW/lmTy/XWBF+vq+pqszWrRos+4joISQn1CKbLW6o6n7tDrFrxOJ7Wc5DoOCoDaBD+LrYupcm6lZr59pusoZY1LFlByUqk+7d//bc2Z8z5VVy9xHQcACmpzbLN3N9upV7mOAqDMpHpSOvizg5pzxRyFKmgbXOK7j5Kzb9/NyuXiOuGEz7qOAgAF9/zdbKu4mw1AcXWv75bNWLZG+gBNG0pKJnNI+/Z9Xc3Nl6i2dqXrOABQUGOZMa3fsl7vbHunZlazNQlA8VhrFbsjpvoz6lW7stZ1nLJH04aSsn//LcpkBtXa+teuowBAwf1sx8+8u9nYGgmgyEY2j2h0yyirbD5B04aSkc0m1NX1Nc2c+XbV17/WdRwAKLh1T3l3s71t6dtcRwFQZmLrYjJRo9mXzXYdBaJpQwk5cOA2pdM9rLIBKAvdI916cMeD3M0GoKiSXUk994/PKbYupuZ3Nisyk7vZ/CDvI/+BQsjlUurq+pIaGtZqxow3uo4DAAXH3WwAiiWbzKrvP/oUuz2mgV8MSFZq/ONGLfk8U7r9gqYNJaG7e73Gxrq0fPl3ZAxX2QAINu5mA1Bo1loN/25Ysdtj6vlBjzKDGUVPiKr1b1s198q5ql5S7ToiXoSmDb5nbVZ79nxBdXWnadasc1zHAYCCm7ib7Vvv+JbrKAACJtWbUvdd3YrdHtPoM6MKVYXUfEmz5n1wnhr/uFEmxMNxP6Jpg3Px+A6Njm5RNLpA0ehCRSJzFAq98Fuzt/fHSiR2aOXKe1hlA1AW7nzqTlWGK3XZyZe5jgIgAHKZnA4+dFCx22Pq/2m/bMaq/ox6Lf/2crW8p0WRRs6t+R1NG5zbvv1qHTr0mxd9JqTKyrmKRhcqGl2gkZHNqq5eoZaWi51lBIDJGEgM6JRbTpGV1aKGRVo0Y5EW1i/UohmLXvi4YaHm1c07YshIKpvibjYAeTG6bVSxO2KKfT+mdHdakdkRLfzEQs29aq5qV3H3WimhaYNT1lrF41vV3PwuzZ17pcbG9imV2qexsX0aG9ureLxd2eyoli//ioxhehqA0rDz4E7tG96ns5ecrZAJaUv3Fj2440HF0/GX/LywCWt+/fznm7hFDYuUzCTVn+jXVa++yk14AIHw3D88p+f+7jmZCqOm85s09+q5mnXuLIUiDI8vRTRtcCqd7lcmM6gZM9aqufkC13EAIC96472SpBvPvlFnLjxTkveQaiA5oL2H9qprqEtdh7q8Hx/qUtdQlzYf2Kz72+9XMpNU64xWve1E7mYDMHXDm4ZV/apqnfab01Q5u9J1HEwTTRucSiR2SJJqapY7TgIA+dM76jVts2tfuJTWGKNZ1bM0q3qWVs9ZfdRfZ61Vf6JfleFKVYT4KxrA1GVHsqqcX0nDFhD8jQCnEokOSVJ19TLHSQAgf3pGeyRJLTUtk/p1xhg11zQXIhKAMpMdySrSwoCRoGBTK5yKxzskhVVVxeWNAIKjN96raDiquso611EAlKnscFbhOuYBBAVNG5xKJHaounqpQiGeBAEIjt54r1pqW7imBIAz2RGatiChaYNT8XgHWyMBBE7PaM9LzrMBQLHRtAULTRucsdYqkdjBEBIAgdM72jvp82wAkC/WWpq2gKFpgzOp1H7lcnFVV9O0AQiWie2RAOCCTVnZjKVpCxCaNjjjDSFh3D+A4GGlDYBL2ZGsJNG0BQhNG5xh3D+AIIqn4xpNj3KmDYAzNG3BQ9MGZ+LxHQqFqhSNLnQdBQDyZuJibVbaALhC0xY8NG1wJpHwJkcaw29DAMHRGx9v2jjTBsARmrbg4d0ynGHcP4Ag6hntkSS2RwJwhqYteGja4EQul1Ey2ckQEgCBw/ZIAK7RtAUPTRucGBvbLWvTjPsHEDhsjwTgGk1b8NC0wYmJcf9sjwQQNL2jvaoMV6q+st51FABliqYteGja4MTEuH+2RwIImp54j2bXzpYxxnUUAGWKpi14aNrgRDy+Q+HwDEUibB8CECxcrA3AteebthqatqCgaYMTiUSHamqW8SQaQOD0xns5zwbAqexIVqGakEyY91lBQdMGJ7xx/2yNBBA8PaM9rLQBcCo7kmVrZMDQtKHostmkxsb2cJ4NQCD1jvZyRxsAp2jagoemDUWXTP5BkmVyJIDASaQTGk2PstIGwCmatuChaUPRvTDun5U2AMHCHW0A/ICmLXho2lB0icQOSVJNDSttAIKlZ7RHktgeCcCp7EhW4XqatiChaUPRxeMdikRmq6JihusoAJBXvaPjK21sjwTgECttwUPThqLzxv2zNRJA8LA9EoAf0LQFD00bii6R2MF5NgCBNLE9kpU2AC5lhjM0bQFD04aiymQOKZWKsdIGIJB6R3tVGa5UQ7TBdRQAZYyVtuChaUNRTQwhYdw/gCDqjfeqpaZFxhjXUQCUqVw6JztmadoChqYNRRWPTzRtrLQBCJ7eeC/n2QA4lR3NShJNW8DQtKGoEokOSUbV1Se6jgIAedcz2sN5NgBOZUdo2oKIpg1FFY93KBpdpHC42nUUAMi73tFe7mgD4BRNWzDRtKGoGPcPIMgmzrQBgCs0bcFE04aisdYy7h9AYCXSCY2kRjjTBsApmrZgomlD0aTTfcpkBpkcCSCQJi7WZnskAJdo2oKJpg1F4w0hEdsjAQRS76jXtLE9EoBLNG3BRNOGomHcP4Agm1hpY3skAJdo2oKJpg1Fk0h0yJgKVVUtdh0FAPKuZ7RHEittANyiaQsmmjYUTTzeoaqqpQqFKlxHAYC8m9geyZk2AC4937TV0rQFCU0biiaR2MF5NgCB1RvvVSQUUUO0wXUUAGUsO5KViRqFIrzNDxL+b6IovHH/O5kcCSCwekZ71FLbImOM6ygAylh2JMvWyAAqSNNmjDnHGNNujNlpjPlsIV4DpcUYoze8IabW1s+5joIyR31CoXCxNqaD2oR8oWkLprwfLjLGhCV9U9LbJO2V9IQx5n5r7bZ8vxZKS0VFvesIKHPUJxTSuovWaSQ14joGShC1CflE0xZMhVhpO0PSTmttp7U2JemHki4qwOsAwGRRn1AwTTVNam1sdR0DpYnahLxpekeT5l4513UM5FkhxvgtkNT1oo/3Snrd4T/JGHONpGsk6YQTTihADAA4wivWJ2oTAAd474S8mffBea4joACcDSKx1t5qrV1jrV3T0sIZAAD+QG0C4FfUJ6B8FaJp2ydp0Ys+Xjj+OQBwjfoEwI+oTQCOqRBN2xOSlhljlhhjKiVdJun+ArwOAEwW9QmAH1GbABxT3s+0WWszxpiPSfpPSWFJt1trt+b7dQBgsqhPAPyI2gTglRRiEImstQ9KerAQXxsApoP6BMCPqE0AjsXZIBIAAAAAwCujaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB+jaQMAAAAAH6NpAwAAAAAfo2kDAAAAAB8z1lrXGWSM6ZW0O89ftllSX56/Zr6RMT/ImB/5zthqrW3J49crOmqTr5ExP8o1I/XpSOX6eyHfSiGjVBo5yzHjy9YmXzRthWCM2WStXeM6x7GQMT/ImB+lkDEISuH7TMb8IGN+lELGICiF7zMZ86cUcpLxpdgeCQAAAAA+RtMGAAAAAD4W5KbtVtcBjgMZ84OM+VEKGYOgFL7PZMwPMuZHKWQMglL4PpMxf0ohJxlfJLBn2gAAAAAgCIK80gYAAAAAJY+mDQAAAAB8LHBNmzHmHGNMuzFmpzHms67zHM4Ys8gY89/GmG3GmK3GmOtcZ3o5xpiwMWazMeanrrMcjTGm0RhzrzFmuzHmWWPM611nOpwx5pPj/5+fMcb8wBhT5TqTJBljbjfG9BhjnnnR52YZY35ujNkx/u+ZLjMGEfUpP/xemyTq0zQyUZscoDblj9/rE7Vpypmc16ZANW3GmLCkb0o6V9JKSe81xqx0m+oIGUmfstaulHSmpI/6MOOE6yQ96zrEMfyrpIettW2SXi2fZTXGLJD0cUlrrLUnSwpLusxtquetk3TOYZ/7rKRfWmuXSfrl+MfIE+pTXvm9NknUp6laJ2pTUVGb8s7v9YnaNDXr5Lg2Bappk3SGpJ3W2k5rbUrSDyVd5DjTS1hrD1hrnxz/8bC8PywL3KY6kjFmoaTzJH3XdZajMcbMkPQmSbdJkrU2Za0ddJvqqCokVRtjKiTVSNrvOI8kyVr7iKSDh336Ikl3jv/4TknvLGqo4KM+5YHfa5NEfZoOapMT1KY88Xt9ojZNnR9qU9CatgWSul708V758A/1BGPMYkmnSXrMbZKjuknSZyTlXAd5GUsk9Uq6Y3wbwneNMbWuQ72YtXafpK9I2iPpgKQha+1/uU11THOstQfGfxyTNMdlmACiPuWH32uTRH3KN2pTYVGb8sfv9YnalF9FrU1Ba9pKhjGmTtKPJX3CWnvIdZ4XM8acL6nHWvs711mOoULSayTdYq09TdKofLZlZnxv80XyiuR8SbXGmMvdpjo+1rsLhPtAypRf61OJ1CaJ+lQw1Kby5tfaJJVMfaI2FUgxalPQmrZ9kha96OOF45/zFWNMRF7RWW+t3eA6z1GslXShMeY5edskzjbG3OU20hH2StprrZ140navvELkJ2+VtMta22utTUvaIOkNjjMdS7cxZp4kjf+7x3GeoKE+TV8p1CaJ+pRv1KbCojblRynUJ2pTfhW1NgWtaXtC0jJjzBJjTKW8g4v3O870EsYYI28v8bPW2q+5znM01tq/stYutNYulvc93Git9dVTDmttTFKXMWbF+KfeImmbw0hHs0fSmcaYmvH/72+Rzw78HuZ+SVeO//hKSfc5zBJE1KdpKoXaJFGfCoDaVFjUpjwohfpEbcq7otamikJ+8WKz1maMMR+T9J/yps3cbq3d6jjW4dZKukLSFmPMU+Of+2tr7YMOM5WqP5e0fvwvmU5JVzvO8xLW2seMMfdKelLe5KvNkm51m8pjjPmBpDdLajbG7JX0d5K+KOlHxpgPSdot6d3uEgYP9ansUJ+mgNpUfNSmskNtmgI/1CbjbcEEAAAAAPhR0LZHAgAAAECg0LQBAAAAgI/RtAEAAACAj9G0AQAAAICP0bQBAAAAgI/RtAEAAACAj9G0AQAAAICP/X+lw1IBS9qbiQAAAABJRU5ErkJggg==\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
}, | |
{ | |
"output_type": "display_data", | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 1080x1080 with 6 Axes>" | |
] | |
}, | |
"metadata": { | |
"tags": [], | |
"needs_background": "light" | |
} | |
} | |
] | |
} | |
] | |
} |
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Hello, thank you for your amazing work of Autobot architecture. I tried this code in my server but I found the code run very slowly on gpu(about 800+ min per epoch), especially the calculation of MultivariateNormal in the loss part(one need at least half a minute). I wonder if this is some version problems since my torch version is 1.8.0 and torchvision version is 0.9.0. Thank you again for your attention.